Community engagement, environmental education, and public

Transcription

University of Louisville
ThinkIR: The University of Louisville's Institutional Repository
Uof L Electronic Theses and Dissertations
5-2015
Community engagement, environmental
education, and public outreach in sustainable
engineering : a collaborative demonstration project
for water treatment using natural processes and
sustainable materials.
Venkata Durga Prasad Gullapalli
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Recommended Citation
Gullapalli, Venkata Durga Prasad, "Community engagement, environmental education, and public outreach in sustainable engineering
: a collaborative demonstration project for water treatment using natural processes and sustainable materials." (2015). UofL Electronic
Theses and Dissertations. Paper 2018.
http://dx.doi.org/10.18297/etd/2018
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COMMUNITY ENGAGEMENT, ENVIRONMENTAL EDUCATION, AND
PUBLIC OUTREACH IN SUSTAINABLE ENGINEERING –
A COLLABORATIVE DEMONSTRATION PROJECT FOR WATER
TREATMENT USING NATURAL PROCESSES AND SUSTAINABLE
MATERIALS
By
B. Tech, Acharya Nagarjuna University, 2006
MS, University of Louisville, 2008
A Dissertation
Submitted to the Faculty of the
J. B. Speed School of Engineering of the University of Louisville
in Partial Fulfillment of the Requirements for the Degree of
Doctor of Philosophy in Civil Engineering
Civil and Environmental Engineering
Louisville, Kentucky
May 2015
PUBLIC OUTREACH IN SUSTAINABLE ENGINEERING A COLLABORATIVE DEMONSTRATION PROJECT FOR WATER
MATERIALS
By
B. Tech, Acharya Nagarjuna University, 2006
MS, University of Louisville, 2008
A Dissertation Approved on
February 5th, 2015
by the following Dissertation Committee:
__________________________________
Dr. Mark N. French
__________________________________
Dr. Nageshwar R. Bhaskar
__________________________________
Dr. Thomas D. Rockaway
___________________________________
Dr. Gail W. DePuy
___________________________________
Dr. Gerold A. Willing
ii
ACKNOWLEDGMENTS
I would like to acknowledge the following individuals for their assistance and
support through completion of this project: Council Woman Tina Ward-Pugh, 9th
District council woman, Louisville, Ky, for providing financial support and having
this project at the Beargrass Falls; Mr. Russell A. Barnett, Director, KIESD, for his
financial support, helping in acquiring materials and construction and for his guidance
at every phase of this project;
Dr. Deborah Yoder-Himes, Assistant professor,
Department of Biology for training us in microbiological testing, and providing us
with materials and facilities for microbial testing; Dr. David Wicks, project manager,
Beargrass Falls, for helping us in construction and organizing educational programs;
Mr. Daren Thompson, MSD Louisville, Ky for helping us in construction and
providing us help at every phase of the project when required; Mr. Daniel Carter,
Plumber foreman, University of Louisville, for helping us in installing plumbing
components; Dr. Eugene Mueller, Professor, Dept. of Chemistry, for helping us in
learning about the bio-safety level certifications; Ms. Ellen Briscoe, and Mr. Jake
Robertson, UofL foundation, for providing space for pre-construction preparations;
Mr. Bernie Miles, Civil and Environmental Engineering Dept. for his help in the lab
and at the site; Dr. Hima Bindu Vuddaraju, Dr. Govardhan Veerareddy Gari, and Mr.
Sam Abdollahian for making it easy to me in learning about microbiological
practices, helping me in water sample collection, analysis, and maintenance of the
pilot project; Mr. Kushal Patel, Mr. Nithin K. Voruganti, for their help in setting up
filters, painting the troughs, and providing transportation when required; Mr. Tegjyoth
Singh Sethi, Mr. Anuteja Mallampati and Mr. Naga sai Chalasani for their help in
statistical analysis of the results.
iii
I am also thankful to Dr. J.P. Mohsen, Civil and Environmental Engineering
Department chair, and Dr. Zhihui Sun, Director of graduate studies for providing me
with financial support for completion of my degree and for the dean’s citation award.
I am also thankful to Prof. Gail W. DePuy, Department of Industrial
Engineering, Prof. Gerold A. Willing, Prof. Nageswar R. Bhaskar, Department of
Civil and Environmental Engineering and Prof. Thomas D. Rockaway, Department of
Civil and Environmental Engineering for their service as members of my doctoral
dissertation committee and also for their valuable inputs and continuous support
throughout the length of the research.
And special acknowledgements to Prof.
Thomas Rockaway for taking extra effort in gathering committee members’
comments and updating us, which helped us to perform our duties more efficiently. I
am also thankful to Prof. Mark N. French, Department of Civil and Environmental
Engineering for his continuous guidance and support throughout this project and as
my dissertation director.
iv
ABSTRACT
PUBLIC OUTREACH IN SUSTAINABLE ENGINEERING –
A COLLABORATIVE DEMONSTRATION PROJECT FOR WATER
MATERIALS
Venkata D. Gullapalli
May 08, 2015
Community engagement through environmental education for the public is an
important component in the link between individual citizens, their community, and
local government agencies responsible for maintaining urban recreation and park
areas. Streams and waterways passing through urban areas are often misunderstood
by the public in terms of whether the waterway is natural, constructed, or a
combination of both. Additionally, aspects of water quality or water pollution are
often obscure to the community and there are limited means to provide direct
information to the public. In any case, the public are often drawn to interact with
urban streams through recreation activities or through environmental education
interest.
It is with this concept in mind that this project was formulated and realized
through collaboration between the Louisville Metro Government Metro-Council, the
local water supply utility Louisville Water Company (LWC), the local stormwater and
sewerage agency Metropolitan Sewer District (MSD), and the University of
Louisville (UL), Kentucky Institute for the Environment and Sustainable
Development
(KIESD).
Project
collaborators
include
Louisville
Metro-
Councilwoman Tina Ward-Pugh; Mr. Greg Heitzman, LWC/MSD; Mr. Daren
Thompson, MSD; and UL personnel: Mr. Daniel Carter, Dr. Deborah Yoder-Himes,
v
Ms. Ellen Briscoe, Mr. Jake Robertson; and Mr. Russell A. Barnett and Dr. David
Wicks, KIESD.
The pilot water treatment plant consists of filters, which uses sunlight for
disinfection and naturally available materials in filters. Disinfection of water by
exposing it to sunlight is an age old concept. Historically containers with water were
left in sunlight for hours to make it potable. Though it was a religious practice in
those days. It started attracting researchers from early 80s to develop sustainable
water disinfection concepts for under developed communities. Most of the research
studies developed systems which involves both thermal and optical inactivation of
bacteria. Researchers are working on increasing the robustness of the systems by
adopting different reflective surfaces and shapes of the reflectors.
Water depth,
suspended solids in water are the major factors which impact the penetration of
sunlight. Reduction of suspended solids can be achieved either by sedimentation or
filtration. Filters comprised of naturally available material can make the system more
sustainable and less expensive.
This project tests the optical disinfection capacity of sunlight. For this an open
channel flow of water was adopted. Four filters were installed to reduce the amount
of suspended particles entering into the solar disinfection system (SODIS). This pilot
study was conducted using polluted urban stream water at 4 different water flow rates.
It is observed that reduction in flow rates resulted in increased disinfection rates. And
filters also contributed in reducing the bacterial concentration. SODIS is successful in
achieving the minimum 30-day average E. coli concentrations in water accessed for
recreation.
vi
TABLE OF CONTENTS
ACKNOWLEDGMENTS ............................................................................................. v
ABSTRACT .................................................................................................................vii
LIST OF FIGURES ...................................................................................................... xi
LIST OF TABLES ....................................................................................................... xv
1
INTRODUCTION .................................................................................................. 1
2
LITERATURE REVIEW AND PROJECT SIGNIFICANCE............................... 5
2.1
INTRODUCTION ................................................................................................. 5
2.2
WATER TREATMENT ........................................................................................ 5
2.2.1 Introduction ................................................................................................. 5
2.2.2 Sedimentation, and Sedimentation with Coagulation, Flocculation............ 6
2.2.3 Filtration ...................................................................................................... 7
2.2.3.1 Slow Sand Filtration ............................................................................. 8
2.2.4 Disinfection ............................................................................................... 12
2.2.4.1 Chemical Disinfection ........................................................................ 12
2.2.4.2 Non-Chemical Disinfection................................................................ 14
2.3 H YDRAULICS AND D ESIGN OF S LOW S AND F ILTER .............................. 17
2.3.1 Introduction ............................................................................................... 17
2.3.2 Hydraulics and Design............................................................................... 18
2.3.3 Maximum Surface Area of Sand Bed ........................................................ 21
2.3.4 Depth of Sand Bed ..................................................................................... 22
2.3.5 Particle size ................................................................................................ 22
2.4
FILTER MEDIA ................................................................................................ 23
2.4.1 Sand ........................................................................................................... 24
2.4.2 Activated Carbon ....................................................................................... 24
2.4.3 Anthracite .................................................................................................. 24
2.5
SOLAR RADIATION ......................................................................................... 25
2.6
SOLAR DISINFECTION (SODIS) ...................................................................... 27
2.6.1 Bacterial Inactivation Mechanism by UV ................................................. 27
2.6.2 Bacterial Inactivation in Solar Disinfection Reactors ............................... 29
2.6.2.1 Thermal Inactivation .......................................................................... 29
2.6.2.2 Optical Inactivation ............................................................................ 30
2.6.2.3 Combined Thermal and Optical Inactivation ..................................... 31
2.6.2.4 SODIS Systems .................................................................................. 31
2.7
SODIS PROJECTS REVIEW ............................................................................. 33
2.8
E. COLI ........................................................................................................... 40
2.8.1 Qualitative Analysis of water for E. coli ................................................... 41
vii
2.8.2 Quantitative analysis of water for E. coli .................................................. 42
2.8.2.1 MI Agar method ................................................................................. 43
2.9
PROJECT SIGNIFICANCE .................................................................................. 45
3
MATERIALS AND METHODS ......................................................................... 46
3.1
INTRODUCTION ............................................................................................... 46
3.2
PROJECT SETUP .............................................................................................. 46
3.2.1 Water Pump, PV Panels, and Storage Tank .............................................. 47
3.2.2 Filtration .................................................................................................... 48
3.2.2.1 Sand .................................................................................................... 49
3.2.2.2 Oyster Shells ...................................................................................... 49
3.2.2.3 Activated Charcoal ............................................................................. 50
3.2.3 Solar Disinfection (SODIS) ....................................................................... 52
3.3
CONSTRUCTION .............................................................................................. 55
3.4
OPERATION .................................................................................................... 57
3.5
RAW WATER FOR EXPERIMENTS .................................................................... 58
3.6
SAMPLING AND TESTING ................................................................................ 58
3.6.1 Sample Collection...................................................................................... 58
3.6.2 Microbial Analysis .................................................................................... 60
3.6.3 Physical Water Analysis ............................................................................ 62
3.7
METEOROLOGICAL DATA ............................................................................... 63
4
METEOROLOGICAL DATA ............................................................................. 65
4.1
INTRODUCTION ............................................................................................... 65
4.2
SOLAR RADIATION MEASUREMENT ............................................................... 65
4.2.1 Direct Normal or Beam Irradiance ............................................................ 66
4.2.2 Diffuse Horizontal Irradiance .................................................................... 66
4.2.3 Global Horizontal Irradiance ..................................................................... 66
4.3
SEASONAL VARIATIONS OF THE SOLAR RADIATION ....................................... 67
4.4
HOURLY VARIATIONS OF SOLAR RADIATION DURING THE DAY..................... 69
4.5
CLOUD COVER ............................................................................................... 74
5
RESULTS AND DISCUSSION ........................................................................... 83
5.1
INTRODUCTION ............................................................................................... 83
5.2
FILTRATION PERFORMANCE ........................................................................... 83
5.2.1 Filter 1........................................................................................................ 84
5.2.2 Filter 2........................................................................................................ 87
5.2.3 Filter 3........................................................................................................ 90
5.2.4 Filter 4........................................................................................................ 93
5.2.5 Filtration discussion ................................................................................... 96
5.3
SOLAR DISINFECTION (SODIS) ...................................................................... 97
5.3.1 Phase I........................................................................................................ 98
5.3.2 Phase II .................................................................................................... 102
5.3.2.1 Scenario I.......................................................................................... 102
5.3.2.2 Scenario II ........................................................................................ 116
5.3.2.3 Scenario III ....................................................................................... 130
5.3.3 System Discussion ................................................................................... 143
viii
5.4
5.5
CONCLUSION ................................................................................................ 145
RECOMMENDATIONS AND FUTURE WORK.................................................... 148
REFERENCES .......................................................................................................... 150
APPENDIX A ............................................................................................................ 157
APPENDIX B ............................................................................................................ 165
APPENDIX C
202
CURRICULUM VITA……………………………………………………………..208
ix
LIST OF FIGURES
Figure 1-1 Satellite Map of Project ................................................................................ 4
Figure 2-1 Oxygen-Ozone cycle .................................................................................. 26
Figure 2-2 Formation of Pyrimidine Dimers ............................................................... 28
Figure 2-3 CPC Reflector ............................................................................................ 33
Figure 2-4 Conventional Solar Flow reactor ............................................................... 33
Figure 3-1 Project Setup .............................................................................................. 47
Figure 3-2 Panels for Powering Water Pump .............................................................. 48
Figure 3-3 Filter Arrangement Showing Inflow and Outflow Controls ...................... 51
Figure 3-4 Inflow Control into Filters ......................................................................... 51
Figure 3-5 Outflow Control from Filters ..................................................................... 51
Figure 3-6 SODIS Troughs Setup and Out Flow Control............................................ 56
Figure 3-7 Sampling Bottles Closed, Opened and Labelled ........................................ 59
Figure 3-8 Cooler Bag for Transporting Water Samples ............................................. 59
Figure 3-9 0.45 µm Pore Size Cellulose Ester Membrane .......................................... 61
Figure 3-10 Filtration Assembly .................................................................................. 61
Figure 3-11 Plate Loaded with the Membrane ............................................................ 62
Figure 3-12 Incubated Plates with Bacterial Growth ................................................... 62
Figure 3-13 Extech DO610 ExStik II DO/pH Conductivity Kit.................................. 63
Figure 3-14 Straight Line Distance between SDF and Beargrass Falls ....................... 64
Figure 4-1 Measurement of GHI, DHI, and DNI......................................................... 67
Figure 4-2 Solar Zenith Angle ..................................................................................... 67
Figure 4-3 Earth’s Tilt Cause of Season ...................................................................... 68
Figure 4-4 Seasonal Variation of Solar Radiation ....................................................... 69
Figure 4-5 Seasonal Path of Sun .................................................................................. 70
Figure 4-6 Hourly Path of Sun ..................................................................................... 70
Figure 4-7 Hourly Variation of Solar Radiation on First Days of 4 Seasons .............. 73
Figure 4-8 Hourly Variation of Solar Radiation on Second Day of Fall 2013 ............ 76
Figure 4-9 Hourly Relation of Solar Radiation and Cloud Cover in Fall (09-21-2013)
...................................................................................................................................... 76
Figure 4-10 Hourly Relation of Solar Radiation and Cloud Cover in Fall (09-22-2013)
...................................................................................................................................... 76
Figure 4-11 Hourly Relation of Solar Radiation and Cloud Cover in Winter (12-212013) ............................................................................................................................ 77
Figure 4-12 Hourly Relation of Solar Radiation and Cloud Cover in Spring (03-212014) ............................................................................................................................ 77
Figure 4-13 Hourly Relation of Solar Radiation and Cloud Cover in Summer (06-212014) ............................................................................................................................ 78
Figure 4-14 Hourly Variations of Temperature and Solar Radiation in Fall ............... 80
Figure 4-15 Hourly Variations of Temperature and Solar Radiation in Winter .......... 80
x
Figure 4-16 Hourly Variations of Temperature and Solar Radiation in Spring .......... 81
Figure 4-17 Hourly Variations of Temperature and Solar Radiation in Summer ........ 81
Figure 5-1 Filter 1 Performance in Reducing E. coli Concentration ........................... 86
Figure 5-5 E. coli Concentration Changes in Trough 1 when System is Static ......... 100
Figure 5-9 Change in E. coli Concentration in Trough 1 in Scenario I ..................... 104
Figure 5-10 Relation between Water pH and E. coli Concentration Change in Trough
1.................................................................................................................................. 104
Figure 5-11 Relation between water Temperature and E. coli Concentration Change in
Trough 1 ..................................................................................................................... 105
Figure 5-12 E. coli Concentration Changes in Trough 2 when Flow is 32.3gal/hr for
3.5 hrs ......................................................................................................................... 107
2.................................................................................................................................. 107
Figure 5-14 Relation between Water Temperature and E. coli Concentration Change
in Trough 2 ................................................................................................................. 108
3.5 hrs ......................................................................................................................... 110
3.................................................................................................................................. 110
in Trough 3 ................................................................................................................. 111
3.5 hrs ......................................................................................................................... 113
4.................................................................................................................................. 113
in Trough 4 ................................................................................................................. 114
Figure 5-21 Relation between Water pH and E. coli Concentration Change in all
Troughs in Scenario I ................................................................................................. 114
in all Troughs in Scenario I........................................................................................ 115
Figure 5-23 E. coli Concentration Changes in Trough 1 when Flow is 18.8 gal/hr for
6.0 hrs ......................................................................................................................... 118
1.................................................................................................................................. 118
in Trough 1 ................................................................................................................. 119
6.0 hrs ......................................................................................................................... 121
xi
2.................................................................................................................................. 121
in Trough 2 ................................................................................................................. 122
6.0 hrs ......................................................................................................................... 124
3.................................................................................................................................. 124
in Trough 3 ................................................................................................................. 125
6.0 hrs ......................................................................................................................... 127
4.................................................................................................................................. 127
in Trough 4 ................................................................................................................. 128
Troughs in Scenario II ............................................................................................... 128
in all Troughs in Scenario II ...................................................................................... 129
5.0 hrs ......................................................................................................................... 131
1.................................................................................................................................. 132
in Trough 1 ................................................................................................................. 132
5.0 hrs ......................................................................................................................... 134
2.................................................................................................................................. 135
in Trough 2 ................................................................................................................. 135
5.0 hrs ......................................................................................................................... 137
3.................................................................................................................................. 138
in Trough 3 ................................................................................................................. 138
5.0 hrs ......................................................................................................................... 140
4.................................................................................................................................. 141
in Trough 4 ................................................................................................................. 141
Troughs in Scenario III .............................................................................................. 142
xii
in all Troughs in Scenario III ..................................................................................... 142
Figure 5-51 Irradiation Values Distribution .............................................................. 142
xiii
LIST OF TABLES
Table 2-1 SODIS systems and Their Capacity ........................................................................ 36
Table 3-1 Filter Specifications ................................................................................................. 50
Table 3-2 Exposure time summary .......................................................................................... 53
Table 3-3 Flow lengths from volume flow values ................................................................... 55
Table 3-4 Painted Troughs ....................................................................................................... 56
Table 4-1 Seasonal Hourly Solar Radiation at Louisville ....................................................... 72
Table 4-2 Cloud Cover and Solar Radiation on First Days of Seasons ................................... 75
Table 4-3 Hourly Variations of Temperature and Solar Radiation.......................................... 79
Table 5-1 Filter Specifications and Titles ................................................................................ 84
Table 5-2 Filter 1 Performance in E. coli Concentration Reduction in 2014 .......................... 85
Table 5-6 Trough Specifications and Titles ............................................................................. 98
Table 5-7 E. coli Concentration Changes in Troughs 1 and 2 during Static Operation .......... 99
Table 5-8 E. coli Concentration Changes in Troughs 3 and 4 during Static Operation .......... 99
Table 5-9 E. coli Concentration Changes in Trough 1 in Scenario I ..................................... 103
Table 5-10 Water pH and Temperature Changes in Trough 1 in Scenario I ......................... 103
Table 5-11 E. coli Concentration Changes in Trough 2 when Flow is 32.3gal/hr for
3.5 hrs ..................................................................................................................................... 106
3.5 hrs ..................................................................................................................................... 109
3.5 hrs ..................................................................................................................................... 112
Table 5-17 E. coli Concentration Changes in Trough 1 when Flow is 18.8 gal/hr for
6.0 hrs ..................................................................................................................................... 117
Table 5-18 Water pH and Temperature Changes in Trough 1 in Scenario II ........................ 117
6.0 hrs ..................................................................................................................................... 120
6.0 hrs ..................................................................................................................................... 123
6.0 hrs ..................................................................................................................................... 126
xiv
Table 5-25 E. coli Concentration Changes in Trough 1 when Flow is 7.3 gal/hr for 5.0
hrs ........................................................................................................................................... 130
Table 5-26 Water pH and Temperature Changes in Trough 1 in Scenario III ...................... 131
hrs ........................................................................................................................................... 133
hrs ........................................................................................................................................... 136
hrs ........................................................................................................................................... 139
Table 5 33 ANOVA Rersults from Minitab .......................................................................... 145
Table 5 34 Tukey Test Results for Scenario, Irradiance and E. coli Reduction .................... 146
Table 5 35 Tukey-Test Results for Trough Performance ...................................................... 146
Table 5-36 SODIS’ Performance in Achieving NPDES RWQ Report 2012 ........................ 147
Table 5-37 Filters’ Performance in Achieving NPDES RWQ Report 2012 ......................... 147
xv
1 INTRODUCTION
Access to pure water is essential for humans for different uses. Domestic use
and recreational use are the two most water usage approaches of water. Domestic use
involves using water for drinking, cooking, bathing, etc.
Recreational activities
involve swimming, fishing, boating, etc. Historically urban streams were used for
recreational activities and educational centres. Because of the urbanization, urban
streams were neglected and abused by changing the natural alignment, combined
sewer overflows, polluted storm water runoff and much more. These factors made
urban streams polluted and limited their usage as recreational spaces. Water has to be
clean and pure to use it either for domestic or recreational purposes. The purity level
that water has to achieve depends on the choice of usage. Basic example for this is
limits on the bacterial concentration in drinking water (0 colony forming units
(CFU)/100ml, EPA Safe Drinking Water Act, 2009) and recreational water (30-day
average of 128 CFU/100ml, NPDES 2012 recreational water quality report). Various
water treatment methodologies are being adopted to treat water for making it safe to
drink and access it for recreation. Water is treated in different methods to make it
potable. Treatment methods adoption depends on the raw water quality, accessibility
to the technology, resources, and the end user size. For example, techniques used for
waste water (high amount of suspended material, and in some cases high amount of
chemical concentration) treatment is slightly different to the ground water (low
amount of suspended solids); A community in a developed country can have better
1
access to technology and resources than a remote community in an under developed
or developing country. A water treatment plant serving an urban area has to be larger
and faster than a treatment plant that serves a rural community. It may not be possible
to install a modern water treatment facility in under developed communities, or treat
water in an urban stream. Using natural resources to treat water where accessibility to
modern technologies and/or investments are minimal to nothing can help in increasing
water quality with minimal costs and less technical knowledge.
Sand and gravel are commonly available materials for water filtration. Along
with them, an effective and abundant method for water disinfection is exposure to
solar radiation - the radiant energy emitted by the sun. Commercially there are
systems available to generate solar-type radiation for any purposes. Research has
proved the use of ultraviolet (UV) radiation (electromagnetic radiation between
wavelengths 280 nm – 400 nm) and infrared (IR) radiation (electromagnetic radiation
between wavelengths 700 nm – 1 mm), as present in natural solar radiation, can be
effectively utilized for water disinfection. Most of the research studies were carried
out using still water in closed containers. Limited quantitative studies address the
feasibility of water disinfection while flowing. Those results prove the concept of UV
disinfection effectiveness when applied under controlled conditions. One of these
conditions involve usage of transparent tubes and compound parabolic collectors
(CPC) for exposing water to sunlight more effectively. This involves usage of both
thermal and optical energy of sunlight for bacterial reduction in water. This project
evaluated the effect of sun’s optical energy in disinfection. For this, an open channel
flow is adopted for restricting water to reach the temperatures where the disinfection
process starts (38OC). Heat absorbing and light reflecting materials were used for
increasing the solar radiation effect on water. Four different filters were installed
2
prior to solar disinfection (SODIS) system for reducing suspended particles entering
into the SODIS.
The goal of the project was to develop a way to connect the public with the
urban stream, raise community awareness to the water quality conditions, and provide
environmental education through the demonstration of viable treatment methods
available to improve water quality.
The community engagement water treatment project was developed as a
public demonstration of sustainable engineering methods to show how natural raw
water can be processed to remove pollutants and improve water quality. The project
goals included to provide a reliable and robust physical system, to apply standard
water treatment practices where natural and sustainable methods are available, and to
implement innovative techniques for disinfection requiring no chemical or
manufactured energy. The primary water quality parameter selected to evaluate the
effectiveness of the system is the concentration of a common bacteria (E.coli)
typically used in evaluation of municipal drinking and waste water treatment.
To meet the project constraints, the water treatment system was constructed in
a large scale with materials resistant to breakage and with low recoverable or
recyclable value. The location of the project was set in a public park adjacent to an
MSD primary pumping station along the main channel of the primary stream draining
much of the Jefferson County Kentucky region, the Beargrass Creek watershed.
Collaboration between community government agencies took the form of LouisvilleMetro government permission to construct the project on the site of the Karen Lynch
Park in the Butchertown neighborhood, the MSD agency providing access to the
Beargrass Creek along the stream bank upstream of the pumping station, and UL
3
KIESD providing materials and personnel to construct the demonstration water
treatment plant.
The remaining portion of this document focuses on the technical aspects of
water quality evaluation performed as part of the demonstration project. In addition
to that component of the effort, a number of elementary and high school student
groups, and international scholar students visited the project site during the
construction and water quality sampling. This project continues to provide a place for
the local citizens to learn about urban streams, water quality, and water treatment
processes. Figure 1.1 shows the satellite map of project location with the components
marked. The map is downloaded from bing maps (http://www.bing.com/maps/).
Solar Panels
Pilot Water Treatment Project
Figure 1.1 Satellite Map of Project
4
2 LITERATURE REVIEW AND PROJECT SIGNIFICANCE
2.1
Introduction
This chapter gives detailed information about previous research in the field of
water treatment (coagulation, flocculation and sedimentation, filtration, and
disinfection); the hydraulics involved in slowsand filtration (SSF) and slow sand filter
design procedures.
Solar radiation and solar disinfection (SODIS) concepts and
applications are discussed. Characteristics of E. coli, and its role as a biological
indicator of water quality and analyses of water samples for E. coli concentration are
discussed. Designing and testing of this project was done by considering the above
concepts and the significance of this project from the previous research projects is
discussed in the final section of this chapter.
2.2
2.2.1
Water Treatment
Introduction
Process that enables water to achieve the standards either for drinking (Safe
drinking water act in USA) or releasing it into natural streams (National Pollution
Discharge Elimination System, NPDES or State Pollution Discharge Elimination
System in USA) is called water treatment. Treatment procedure that is adopted
depends on the raw water quality at the source and the intended use or application of
the treated water produced. Less energy is required and fewer procedural steps are
typically required to treat ground water relative to any water drawn from surface
sources.
5
In general, there is a standard series of steps in water treatment and the most
common steps involved are (EPA 832-R-12-011):
1. Sedimentation, and Sedimentation with Coagulation, Flocculation
2. Filtration
3. Disinfection
2.2.2
Sedimentation, and Sedimentation with Coagulation, Flocculation
Most surface waters contain suspended and dissolved solids. Sedimentation is
the process of removing suspended solids, through particles settling, while water is
stationary or moving through a tank at a slow rate (World Health Organisation, WHO,
2007). Simple sedimentation is the process of passing water through a tank at a slow
rate allowing suspended solids to fall out of suspension (WHO 2007).
The tank is
sized based on the raw water that has to be treated and also the amount of water that
has to be treated (water drawn from ground water has less suspended particles,
whereas water that has to be treated in wastewater treatment plants contains more
suspended solids). Many simple sedimentation procedures do not remove all finegrained particles because high design flow rates result in an insufficient retention
time. To address this issue, the simple sedimentation process is enhanced through the
addition of chemicals, which are called coagulants (EPA, 2004). Adding of coagulant
chemicals is intended to thicken solids, increasing the mass and density, allowing the
particles to settle more rapidly.
Typically, suspended particles may be negatively
charged and repel each other resulting in no coagulation (EPA 2007).
Coagulants
may be positively charged and effectively neutralize the negative charge of dissolved
and suspended particles in water. The resulting reaction binds sediment particles
together, or coagulates them, forming a mass called the floc (Ayguna, A. 2010). Once
6
the coagulated sediment particles form a floc and flocs reach a critical mass,
overcoming buoyancy, they sink to the bottom of the settle tank. Flocculation is the
rapid mixing of water after the addition of a coagulant.
Mixing circulates the
coagulant throughout water and evenly contacts sediment particles. Most common
compounds used as coagulants are ferric chloride, alum, and aluminium salts (Amuda,
O.S., 2007). Coagulation removes suspended particles, and a large amount of organic
compounds, including some dissolved organic material, which is referred to as
Natural Organic Matter (NOM) or Dissolved Organic Carbon (DOC). However, there
are no limits on presence of DOC, but presence of DOC can give water an unpleasant
taste and odour, as well as a brown discoloration (SDWF 2006). Research studies
show that sedimentation and coagulation remove some pathogens that are attached to
suspended substances (Kawabata, N., 2005).
2.2.3
Filtration
Filtration is the next step in water treatment process.
Some small water
treatment plants that cannot afford the coagulation unit, because of the investment that
involves in setting up coagulation tanks, will directly go for filtration (Pernitsky, D.J.,
2006). The purpose of filtration is to remove fine-grained suspended particles from
water by passing water through a medium. Filtration is usually the final step in the
removal of solids that began with sedimentation and coagulation/flocculation. Most
commonly used filters in small communities and remote communities (communities
that do not have access to technology and low income) are slow sand filters
(Huisman, L., 1974). They are good for serving small communities, because of their
less filtration rate and economic viability (Huisman, L., 1974).
7
2.2.3.1 Slow Sand Filtration
Slow sand filtration process is one of the oldest and widely used method for
small communities to filter water. The treatment process is simple, reliable and an
inexpensive way for water filtration. It requires minimal to zero power for operation
and no chemicals are required. Slow sand filtration reduces bacteria, cloudiness, and
organic contaminant levels in water (Huisman, L., 1974). Particle removal process in
sand filters is categorized into three mechanisms. They are transport, attachment, and
detachment.
Transport
Transport is the process of bringing impurities into contact with the sand grain in
filter media material. Physical properties of the suspended particles influence these
mechanisms (Thames Water and University of Surrey 2005).
The transport
mechanisms include:

Interception
Interception is the contact of a suspended particle to a sand grain in
filter media. This depends on the diameter of the suspended particle and the
pore size of the filter media. This can be achieved only if the particle is
carried by one of the streamlines closest to the media grain (a distance of 0.05
mm or less between the sand grain and streamline) (Ives, K. J., et al., 1975).
Streamlines are those that are drawn to visualize the flow, they are tangential
to the velocity field. Rates of interception increases as the diameter of the
suspended particle increases and the pore size between the media grains
decreases.
8

Inertial Flow
When water flowing in straight-line flows between the media grains,
suspended particles in water with sufficient inertia may swerve off the line of
flow that they are supposed to follow. Due to this, a particle may come in
contact with the sand grain as a result, and attach. Transport via inertia
increases as the surface loading rate (hydraulic loading (flow rate, m3/h) per
unit cross-sectional area of the filter bed (m2)) increases (Ives, K.J., et al.,
1975).

Diffusion
Diffusion is used to describe mass transport via Brownian motion.
Brownian motion is defined as the movement of suspended particles in fluid or
gas medium due to their bombardment by molecules of that fluid or gas.
Thus, there is a transfer of thermodynamic energy to kinetic energy, from the
media molecules to the particles suspended in it (Huisman. L. & Wood W. E.,
1974). In this case, media is raw water flowing into the filters. A suspended
particle will take discrete steps as a result of its collision with water molecules
(Hendricks, D.,, 1991). This results in suspended particle achieving Brownian
motion.
The particle will move from one streamline to another, until
eventually it may collide with a media grain. Diffusion is independent of the
surface loading rate.

Sedimentation
9
This is similar to the process that happens in sedimentation phase of
water treatment process.
Gravitational forces can move particles across
streamlines into quiescent areas on upward-facing surfaces of bed grains.
Larger, denser particles will settle first.
Sedimentation efficiency is the
function of the ratio between the surface loading and the settling velocity of
the suspended particles.
Attachment
Once the suspended particles in water come in contact with a sand particle, there
must be a force present to hold particles in place and achieve removal of the particles.
Process of holding of suspended particles by sand particles is attachment. The main
forces involved in this mechanism are:

Electrostatic Attraction
Particles in suspension and the surfaces of the media grains attract to
each other, if they are oppositely charged. This depends on the age of the
sand. A clean crystal sand grain has a negative charge and is able to attract
positively charged particles. This accumulates positively charged particles to
such an extent that oversaturation may occur with reversal of the charge, and
starts attracting negatively charged particles (Huismans, L et. al. 1974).

Van der Waal’s Forces
Forces present between molecules are Van der Waals forces. These
forces include attraction and repulsion forces present between molecules. The
attractive forces happens when the material in water are at a distance of 0.05
mm or less (Ives and Gregory, 1967). The attractive force between two water
molecules have minor effect in drawing suspended particles together.
10
However, when the particles (Sand grain and suspended particle) get in
contact with each other the attractive forces between water molecules will play
a significant role in ensuring attachment of one to other.

Adhesion
Deposited organic particles quickly become the breeding grounds for
bacteria and other microorganisms that results in creating microbial colonies.
This situation results in the development of a biofilm called Schmutzdecke
(Law, S. P., et al., 2001). This layer helps in trapping the bacteria and
reducing the bacterial concentration leaving the filters. However, this takes a
while to achieve depending on the impurities that flow into the filters.
Detachment
The mechanism of losing attached material to the sand grain is detachment. It is
required to maintain the equilibrium between the factors that help in operating the
sand filters.
In addition, this mechanism is largely influenced by the physical
characteristics of the media, and type and growth of microorganisms in biofilm (van
Loosdrecht et al 1995).
If not maintained, detachment of the particles that are
attached to sand gains, playing key role in water purification happens and this results
in degraded performance of the filter. Factors that make detachment happen are:

Flow Rate Change
High flow rates or sudden changes in flow, combined with deposit
instability may result in detachment. To minimize this, excessive run lengths
and improper flow rates into filters should be avoided. This minimizes deposit
instability and erosion.

Grazing
11
Biofilm may be removed by grazing by macro-fauna and/or predation
of smaller organisms by protozoa (Bryers, J. D., 1987).

Shedding of Biofilm
This happens because of improper cleaning activities and this detaches
microorganisms from biofilm and opens place for a new habitat for
microbiological colonization.
2.2.4
Disinfection
Disinfection is the final step in water treatment process and is done just before
distribution. This step clears the bacterial concentration in water. Disinfection rates
are dependent on the source of water. Most commonly used disinfection methods are
heat, chlorination, ozonisation, UV light and micro-filtration.
The disinfection
methods are categorized into two methods, chemical and non-chemical.
2.2.4.1 Chemical Disinfection
Adding of chemicals to water for killing the bacteria or virus in water is called
chemical disinfection. Most commonly used chemicals for disinfection are chlorine
and ozone. In order for chemical disinfection to be effective, water must be filtered.
Chemical disinfection often leaves an undesirable taste in water, which an activated
carbon filter can remove post-treatment.
Chlorination
Chlorination is the process of adding chlorine to water as a method of water
disinfection that makes it fit for human consumption. Water treated with chlorine is
effective in preventing the spread of disease (EPA, 1986). Chlorine may be used in
gas, liquid or solid form to disinfect water because chlorine gas is highly toxic and
can be dangerous if released into the atmosphere, this form of disinfection must be
12
done in controlled environment. Otherwise, the danger is avoided by the use of
chlorine in liquid form (sodium hypochlorite) or solid form (calcium hypochlorite).
Chlorine when added to water releases hypochlorous acid (HOCl), and hydrochloric
acid (HCl). Depending on the pH, HCl may further breakdown into Hydrogen (H+)
and Hypochlorite (OCl-) ions.
The concentration of hypochlorous acid and
hypochlorite ions in chlorinated water will depend on water's pH. A higher pH
facilitates the formation of more hypochlorite ions and results in less hypochlorous
acid in water. Hypochlorous acid is the most effective form of free chlorine residual,
which is chlorine available to kill microorganisms in water. Hypochlorite ions are
much less efficient disinfectants. So, disinfection is more efficient at a low pH than at
a high pH.
Cl2 + H2O → HCl + HOCl
HCl ↔ H+ + ClWater utilities are moving from using free chlorine to chloramine in their
drinking water disinfection (EPA 1999). Chloramines are made when ammonia is
added to water containing chlorine, or when water-containing ammonia is chlorinated.
Even though chloramines are weaker disinfectants than chlorine, they are used as
disinfectants because; they are more stable and extend disinfection benefits
throughout a water utility's distribution system. Chloramines are not used as the
primary disinfectant for water; but are used for maintaining a higher-level disinfectant
residual in the distribution system for a longer period relative to chlorine.
While chlorine is a highly effective and widely used method of water
disinfection, it reacts with organic compounds in water, forming trihalomethanes
(THMs) and haloacetic acids, which are carcinogenic in large quantities. The best
13
way to avoid this is to remove as many organics as possible, prior to disinfection.
Chloramines do not form THMs or haloacetic acid as chlorine does.
Ozone
Ozone disinfection is gaining popularity because of its better performance than
chlorination in disinfecting water (EPA 1999). Being a powerful oxidizing agent,
ozone is toxic to most waterborne organisms. When ozone is decomposed into water,
hydrogen peroxy (HO2) and hydroxyl (HO) are formed. These have great oxidizing
capacity and results in cell wall disintegration in bacteria.
Ozone is often
accompanied by a secondary disinfectant, such as chlorine. Post-treatment, it leaves
few residuals to prevent the future growth of microorganisms in water. Due to its
highly unstable nature, ozone cannot be transported. Therefore, ozone has to be
generated at the site of water treatment. This requires lots of investment. Though the
contact time required is less when compared to other chemicals and no harmful
residuals are left after treatment, ozonisation has been less used because of its
complex technology and greater power usage. Research is going for making the
technology more viable and adoptable.
2.2.4.2 Non-Chemical Disinfection
Disinfecting techniques of water without usage of chemicals falls in this category.
Boiling
Boiling of water to kill bacteria is an age-old technique that is used in present
days when water may be from a primitive source with unknown treatment or there is a
boil-water emergency (CDC, 2013). Heating water to the boiling point kills diseasecausing microorganisms and is the surest way to make otherwise-clean water safe for
14
drinking. To ensure that all microorganisms are killed, water must boil vigorously for
one minute (CDC 2013).
Membrane Filtration
Membrane filtration is recognized widely as a superior water and wastewater
treatment technique. Membranes provide a physical barrier that effectively removes
solids, viruses, bacteria and other unwanted molecules. Researchers are developing a
variety of membranes for different industries and some are even smart. For example
Lewis, S. R., et al., 2011 developed a membrane that have nano-pores which opens
and closes according to the impurities present in water flowing through the
membrane. Primary advantages of membranes are less space requirement and the
treatment process can be automated.
For example, conventional filter cleaning
practices takes lots of human effort and time to carryout depending on the size of
filter, where as in case of membrane filtration cleaning can be scheduled based on the
filter usage and filter pore clogging.
With the advent of technology, advancing
research in this field is making the membranes more efficient and economical over the
time. Ultrafiltration is a type of membrane filtration that is a pressure‐driven process,
which removes particles by pushing water through a filter medium. Any particles
larger than the filter pore opening are blocked and removed from water.
Ultrafiltration is majorly used for clearing suspended solids, removal of viruses and
bacteria or high concentration of macromolecules in water. This technology is being
applied in many industries like oil, food processing, chemical process, and water
treatment, where separation is required at micro or nano-level (lenntech, web
reference).
15
UV Disinfection
Use of UV based disinfection systems has experienced rapid growth over the
last 2-3 decades (Mbonimpa E.G., et al., 2012), because of low by-products release
and less space for construction. The UV spectrum covers the wavelength range from
100-400 nano-meters (nm), and lies between x-rays and visible light in the
electromagnetic spectrum. UV light with wavelengths between 200-300 nm (UVC)
inactivates most microorganisms. Studies prove a maximum disinfection capacity for
most microorganisms with exposure to UV at 260 nm (EPA 2006). Most of the
synthetic UV light generators contain an inert gas and a small amount of liquid
mercury. The mechanism involved in generating synthetic UV light is by exciting the
mercury atoms to higher energy state. This is done by the collision of free electrons
and ions with the gaseous mercury atoms. Energy that is in the form of UV light that
is in the range of germicidal wavelength (200 – 300 nm) is discharged when the
excited mercury atoms return to their ground, or normal, energy state. The amount of
UV light produced by a synthetic UV lamp is influenced by the concentration of
mercury atoms in the lamp (Clarke, S. H., 2006).
When UV light is transferred from a source (most of the times source is
mercury arc lamp) to an organism’s genetic material, UV penetrates through the cell
wall of an organism and destroys the cells’ ability to reproduce. Microorganisms that
cannot reproduce cannot infect and are thereby inactivated. Limitations to UV water
disinfection include presence of high turbidity, particulate matter, and natural organic
matter (EPA 832-F-99-064).
The advantages of UV disinfection include no significant toxic by-products.
Over dosing, is not an issue as with chemical treatments. Storage or development of
16
harmful chemicals are not required other than proper disposal of UV lamps after
useful life. The contact time for disinfection is much less when compared to chemical
disinfection processes. However, one considerable disadvantage includes the absence
of a disinfection residual to maintain disinfection in a distribution or storage system.
Organism may reverse the inactivation either by “photoreactivation” or by “dark
repair” mechanisms. Photoreactivation is the recovery from biological DNA damage
caused by UVC or UVB radiation by simultaneous or subsequent treatment with light
of longer wavelength (>300nm), a similar mechanism that happens in the absence of
light is called dark repair.
2.3
Hydraulics and Design of Slow Sand Filter
2.3.1 Introduction
Hydraulics involved in slow sand filtration and its design procedures are discussed
in this section. Hydraulic analysis influences the design decisions and plays key role
in a slow sand filter design. Major hydraulic functions involved in a slow sand filter
design are (Huisman, L., et al., 1974):
1. Raw water distribution on the filter without erosion (inflow)
2. Head loss through the filter bed
3. Water collection from filter (Outflow)
4. Control water flow through sand bed
5. Water draining from filter for sand bed maintenance
6. Over flow of filter
17
2.3.2
Hydraulics and Design
Function 1 is about finding the volume of water (m3) that has to be flown into
filter per unit time (hr) per unit area (m2). The amount of water a slow sand filter
filters depends on the Hydraulic Loading Rate (HLR). It is defined as the rate of flow
per unit area. Here, area is the surface area of sand bed and flow is the raw water
flowing into the filter. The ideal HLR values range between 0.1 m/hr to 0.4 m/hr.
Equation 2.1 is for calculating the HLR value.
(2.1)
Where,
HLR = Hydraulic loading rate (m3/m2/s)
Q = Flow of water (m3/s)
A = Plan area of filter bed (m2)
Once water is made to flow into the filter, flow through the filter bed is
assumed to be laminar. A flow is said to be laminar, when the molecules (water
molecules) are flowing in straight and parallel lines. In other words the flow is said
laminar in pipe flow when the Reynolds number (ratio of inertial force to viscous
force, and it is dimension less) of the flow is less than 2000. In general, Reynolds
number (R) is expressed as shown in equation 2.2.
(2.2)
Where,
R = Reynolds number
18
ρ = Fluid density (kg/m3)
V = Mean velocity of the object relative to fluid (m/s)
L = Characteristic length (m)
.
µ = Dynamic viscosity of the fluid (kg/(m s))
Consideration of characteristic length value depends on the flow: for example,
pipe diameter is considered as characteristic length for pipe flow, it is hydraulic radius
in open channel flow. However, for porous media flow it changes because of the
particle size distribution and non-uniform flow paths. Ward (1964) simplified the
characteristic length value in porous media as square root of intrinsic permeability.
Where, intrinsic permeability is the property of the porous media, and basically a
measure of the surface area of the grains in a porous medium.
Equation 2.3 gives the general equation created by Ward (1964) for the
Reynolds number (Rpm) in porous media. In the case of a packed bed, Reynolds
number has to be less than 10 to state the flow as Laminar (Ziolkowska, I. et al.,
1988).
(2.3)
Where,
Rpm = Reynolds number through porous media
v = Superficial velocity synonymous to HLR or specific discharge (q = Q/A)
(m3/m2/hr) standard value between 0.1 – 0.4 m3/m2/hr = 2.78 e-5 – 1.11 e-4
m3/m2/s
k = Intrinsic permeability (m2)
19
(2.3 a)
K = Hydraulic conductivity (m/s) – 2 e-7 to 2 e-4 (value for fine sand, Domenico and
Schwartz 1990)
g = Acceleration due to gravity (m/s2) -- 9.81 m/s2
ρ = Fluid density (kg/m3) – 999.8 kg/m3 for water at 00C; 998.2 kg/m3 at 200C
.
.
µ = Dynamic viscosity of the fluid (kg/(m s)) – 0.001792 kg/(m s) for water at 00C;
0.001003 at 200C
Equations 2.3.1 and 2.3.2 are example calculations of Reynolds number for a
flow through sand bed at 00C and 200C. Substituting the standard values from above
the Reynolds number for a flow through fine sand bed will be:
(
(
)√
(
)(
)(
(
)(
)
)
(
)
)
(2.3.1)
Rpm = 2.97 e-6 < 10
(
(
)√
)(
(
(
)(
)(
)
)
)
(
) (2.3.2)
Rpm = 3.973 e-6 < 10
This condition satisfies Laminar flow conditions. Laminar flows typically
occur when the fluid is highly viscous or the flow velocity is too low. In slow sand
filters the sand bed is expected to have equally distributed pores and pore sizes
because of the uniform sand (particle size) used in it. When water flows through the
sand bed there will be a constant change in direction as the flow leaves one sand grain
and meets the next. In majority of the cases, this satisfies the condition of laminar
flow (water molecules flowing in parallel to each other). With this assumption,
20
Darcy’s law describes the head loss in the sand medium. The HLR value from
equation 2.1 is used to calculate the head loss using the equation 2.3 b.
(2.3 b)
hL = Headloss across sand bed (m)
z = Depth of filter bed (m)
Head loss calculated from above equation is for the initial stages of filter.
This value increases over the period because of the clogging of pores and
development of biofilm called Schmutzdecke. However, helps in removing bacteria
from water, Schmutzdecke may result in improper passage of water into sand bed.
This results in head loss increase and flow not meeting laminar flow conditions.
Laminar flow conditions help in controlling sand erosion and indicates uniformity of
flow through sand bed, which means no blockages in the sand bed. Not satisfying
laminar flow conditions also results in improper outflow volumes. Headloss across
filter bed is measured by using piezometers. An increase in headloss shows the
accumulation of suspended particles or formation and thickening of Schmutzdecke.
2.3.3
Maximum Surface Area of Sand Bed
Flow rate (Q) is determined by water supply demand (average volume of
water required per unit end user per day), this value changes based on the climatic
conditions, and influenced by the type of end user (humans, factories, and irrigation,
etc.) and equation 2.1 is used to determine the area of sand bed required for operation.
The acceptable range of HLR is 0.1 m/hr to 0.4 m/hr (AWWA, 1990).
21
2.3.4
Depth of Sand Bed
Depth of sand bed depends on the desired number of years of operation before
re-sanding. Re-sanding is the process of refilling the sand to replace the sand bed that
is lost because of scrapping (removal of certain depth of top portion of sand bed (few
inches) along with Schmutzdecke to make the filter perform better after clogging). In
addition, researches proved that the deeper the sand beds results in the longer the filter
operations (EPA 1995).
However, to have a deeper sand bed it requires huge
construction.
2.3.5
Particle size
The granular fill material used in the filter must have a range of grain sizes. The
filter is constructed in layers of generally similar grain sizes.
The filter layers are
ordered by grain size with finer grain layers at top and coarser at bottom. The coarser
bottom layers restrict finer particles from entering into the plumbing.
Gradual
increase of particle size from top to bottom achieves the desired mitigation of finer
material entering into plumbing. From their studies, Huisman and Wood (1974), have
suggested five rules for design of the gravel support and AWWA (American Water
Works Association) made those rules as benchmark for the particle size in slow sand
filtration (AWWA 1990). The rules are:
1. d90 (given layer)/d10(given layer) < 1.4
2. d10 (lower layer)/d10(upper layer) < 4
3. d10 (top layer)/d15(sand) > 4
4. d10 (top layer)/d85(sand) < 4
5. d10 (bottom layer)/2 X d (drain orifice diameter) < 1.4
22
AWWA slow sand filtration manual (AWWA 1990) recommends to design and test a
pilot filtration system before designing a full-size system. This helps in learning
about the raw water quality that has to be treated and allows evaluation of locally
available filter materials.
Advantages of slow sand filtration

Effective in improving the bacterial and physical qualities (turbidity) of water

Easy to operate and maintain

No chemicals required

Can achieve 4 log reduction of bacteria at its peak performance
Disadvantages of slow sand filtration

Requires larger space to construct

Vulnerable to clogging if incoming water have high turbidity
Rapid sand filters (RSFs) have the same core mechanism as slow sand filters
(SSF). However, they are more advanced. Some RSFs are multi-media filters, which
include usage of anthracite, granular activated charcoal along with sand and gravel.
Back washing can be done in RSFs for cleaning the filters. Back washing is the
process of passing pure water in the reverse order of filtration. Because of advantages
over slow sand filters, many slowsand filters are being replaced with rapid sand
filters.
2.4
Filter Media
While there are wide variety of filter media available following are materials
used in the potable water industry.
23
2.4.1
Sand
Sand is the most common available filter material. Moreover, it is good to test
the local available sand first as filter bed, because it can be a viable financial option to
use local material than importing it from other places. Sand should be washed prior to
use, and different grades of sand improve the long-term operation of the system.
2.4.2
Activated Carbon
Activated carbon (AC) has been in use in home water purification systems for
removing odour and taste. They are also effective in removing chlorine, sediment,
and volatile organic compounds (VOCs). Activated carbon filtration is an adsorptive
process in which the contaminant is adsorbed onto the surface of the carbon particles.
The efficiency of the adsorption process is influenced by particle and pore size,
surface area, density and hardness of the carbon particle. AC medium used can be
petroleum coke, bituminous coal, lignite, wood products, coconut shell, or peanut
shells.
The carbon medium is “activated” by subjecting it to steam and high
temperature (2300°F) without oxygen (Dvorak, B. I. et al. 2013). It is then crushed
to produce a granular or pulverized carbon product. This creates small particles with
more outside surface area available to which compounds can adsorb, which results in
greater contaminant removal. The source of the carbon and the activation method
determine the effectiveness of removal for specific contaminants. A filter reaches its
capacity when all adsorption sites on the activated carbon become full of
contaminants (EPA 2013).
2.4.3
Anthracite
Anthracite coal is a hard coal with more fixed carbon and less volatile matter
(EPA 1996). Anthracite promotes higher service flow rates and longer filter runs with
24
less head loss than single media filter beds. This reduces the backwashing rates.
Backwashing of filters is a regular process of cleaning filters for cleaning the filter
and make them perform better; this involves flushing water in reverse path to the
regular water filtration path.
Low uniformity coefficient anthracite filter media
extends the life of filter. Because of its high carbon content, Anthracite is the most
common media used in rapid multimedia filters along with sand.
2.5
Solar Radiation
Solar radiation is the electromagnetic radiation emitted by the sun.
Solar
radiation has many bands in it. However, the significant band of radiation is divided
into five regions in ascending order of wavelengths (Naylor, M. F., et al., 1995).
These band regions are UVC (100 – 280 nm), UVB (280 – 315 nm), UVA (315 – 400
nm), Visible Light (380 – 780 nm), IR (700 - 106 nm). Visible light or visible range
is that visible to human eye and that is not visible to naked eye is non-visible range or
light. In nature UVC is blocked by stratospheric oxygen and no amount of UVC
radiation reaches the earth’s surface, mechanism involved behind this is, an oxygen
(O2) molecule is split into two oxygen (O) atoms being hit by high frequency UV
light (UVC and UVB). These atoms then combine with O2 molecules to form ozone
molecule (O3) (Newman, P.A 1999).
Figure 2.1 shows the atmospheric Ozone-
Oxygen cycle (Newman, P.A 1999).
More than 90% of the UVB radiation is
absorbed by ozone (Amaro-Ortiz A., et al., 2014). Infrared radiation in solar radiation
is the primary cause for temperature increase in the atmosphere. The temperature
increase depends on the Carbon dioxide (CO2) concentration in atmosphere.
25
Clouds reduce the amount of solar irradiance reaching the Earth's surface
although changes in the ultraviolet region are not as great as those of total intensity
(Diffey, B. L., 1991). The effect of cloud cover on solar radiation reaching earth’s
surface depends on the cloud layers and cloud types. Huge storm clouds can almost
eliminate terrestrial UVR (Ultra Violet Radiation) even in summer time (Diffey, B.
L., 1 991).
Figure 2.1 Oxygen-Ozone cycle
Reflection of solar radiation from ground surfaces, including the sea, is
normally low (<7%) and is high for fresh snow (fresh snow can reflect up to 80 per
cent of incident solar radiation). This proves that more than 7% of solar radiation
cannot be reflected from water surface and it can be absorbed by water. Penetration
of solar radiation is dependent on the turbidity levels of water. Altitude is another
factor that affects the solar radiation, each 1 km increase in altitude increases the
ultraviolet flux by about 6%, i.e. places on the Earth‘s surface below sea level are
relatively poorer in receiving solar radiation than sites that are at sea level or higher
elevation (Cutchis, P., 1991). Louisville region’s elevation ranges from a high of
26
about 761 feet and to a low of 382 feet above sea level (elevations and distances in
the United States, USGS) and so suffices as a suitable location for utilization of
natural UV irradiance for water disinfection.
2.6
Solar Disinfection (SODIS)
Solar disinfection (SODIS) is the process of disinfecting water by exposing it to
sunlight. Descriptions of solar disinfection of water have existed in communities on
the Indian sub-continent for nearly 2000 years.
In the distant past, drinking water
was placed outside in open containers to be “blessed” by the sun (Baker, M.N.T.M.,
1981). Downes and Blunt (1877) proved that sunlight is effective in reducing or
killing the bacteria. Disinfection by sunlight happens because of the UV radiation and
infrared radiation present in solar radiation (Mbonimpa, E. G., et al., 2012). The
shorter the wavelength the stronger is its disinfection capacity, based on this UVC is
considered as the strongest disinfectant. Stratospheric oxygen absorbs all the UVC
and 90% of the UVB radiation and 5-10 % of UVA reaching earth’s surface. This
creates a situation that UVA and UVB are available for disinfection.
2.6.1
Bacterial Inactivation Mechanism by UV
The inactivation mechanism involved in artificial UV (UVC is generated and
used from vapor lamps) and natural UV (UVB and UVA) are slightly different
(Caslake, L. F., et al., 2004). The basic mechanism involved in UVB and UVC
disinfection is formation of pyrimidine dimers. When bacterial DNA absorbs UVB or
UVC radiation thymine base pairs in genetic sequences bond to each other and forms
pyrimidine dimers. This is a disruption in the strand, which reproductive enzymes
cannot copy (Goodsell D.S., 2001).
Figure 2.2 (http://www.bath.ac.uk/) shows the
pyrimidine dimers formation before and after absorption of UV by DNA. Formation
27
of Pyrimidine dimers results in making the bacteria incapable to reproduce and this
reduces infection capacity of the bacteria. Unable to multiply, pathogens no longer
pose a health risk and soon die. UVB (wavelength of 280-315 nm) being in the
germicidal range (200-300 nm) is capable of causing DNA damage.
Figure 2.2 Formation of Pyrimidine Dimers
Although the UVA wavelengths (315-400 nm) are not sufficiently energetic to
directly modify DNA bases, they play an important role in formation of reactive
oxygen species (ROS) such as singlet oxygen, superoxide, hydrogen peroxide, and
hydroxyl radical (Jagger, J 1981; Eisenstark, A 1987; Lloyd, R. E. et. al. 1990;
Sammartano, L.J., 1987; Tuveson, R. W. et al. 1986). Once formed, these ROS can
cause damage to DNA. Additionally, sunlight can be absorbed by natural exogenous
photosensitizers present in surface waters (humic acids and chlorophyls), which in
turn can react with oxygen to produce ROS (Blough,N.V.
et al.
1995;
Schwartzenbach, R.P., et. al., 2003) which can exert a disinfecting effect. Berney
(2006) and Bosshard (2010) studied damaging effects of sunlight on cell protein.
28
They pointed out that solar photons attack proteins, directly or indirectly via ROS,
and this could be the main mechanism of action during solar disinfection. Hamamoto
A. et. al. 2007 developed a water disinfection system using UVA light-emitting
diodes, discovered that UVA radiation is effective in reducing and inactivating the
bacteria.
Several SODIS systems, or reactors, are developed considering UVB or UVA
radiation and IR. When using the solar radiation as source for disinfection, UVA is
abundantly available in natural sunlight and is able to penetrate deeply (Lee, Z et. al.
2013).
2.6.2
Bacterial Inactivation in Solar Disinfection Reactors
Inactivation of the bacteria under solar radiation occurs in three ways.
1) Thermal inactivation.
2) Optical inactivation.
3) Combined thermal and optical inactivation.
2.6.2.1 Thermal Inactivation
Thermal inactivation is a process of inactivating the bacteria by application of
heat. This is one of the oldest techniques for water disinfection. This significantly
improves the microbiological quality of water, but does not fully remove the potential
risk of waterborne pathogens if water temperatures do not reach boiling point (Rosa et
al. 2010). Infrared radiation is another region in solar radiation and not visible to
naked eye, but the heat produced by radiation in wavelengths beyond 700nm is sensed
as heat. The infrared radiation absorbed by water is responsible for increasing its
temperature.
Microorganisms are sensitive to heat, and water can experience a
29
bacterial reduction of 99.9% prior to reaching a boil temperature.
This can be
achieved by heating up water to 50-60°C for one hour (SANDEC, 2002).
In solar disinfection, water is retained in airtight containers to increase the
water temperature. A number of enhancement methods have been attempted by
accelerating the rate of thermal inactivation of organisms using absorptive materials
and painting the containers black (Sommer, B. et. al., 1997) in order to aid in the
absorption of solar radiation.
Thermal enhancement has been achieved by: (i)
painting sections of the bottles with black paint (Martin-Dominguez, A. et al. 2005);
(ii) circulating water over a black surface in an enclosed casing that was transparent to
UVA light (Rijal, G.K et al. 2003); (iii) using a solar collector attached to a double
glass envelope container (Saitoh, T.S., El-Ghetany, H.H. 2002). Solar reflectors can
also increase the temperature of water but not to the same extent as the use of
absorptive materials or blackening of bottles (Mani, S.K. et al. 2006).
2.6.2.2 Optical Inactivation
Optical inactivation of bacteria is a process of inactivating bacteria by
application of optical irradiation.
irradiation.
In this case, solar irradiance is the optical
The incident solar irradiance on the outer Earth atmosphere has an
intensity of approximately 1360 W/m2. This value varies with position within the
elliptical sidereal orbit of the Earth (the path that earth follows to revolve around the
sun during a day or month or season) as it orbits the Sun. The irradiance intensity on
a horizontal surface at ground level on the equator is reduced to roughly 1120 W/m2
(averaged over the period of hours during which sunlight is available) after it gets
absorbed by atmospheric components including water vapour, ozone, oxygen, and
others. Thus, 1.12 kJ/m2 (1.12 kj/m2 = 1120 W/m2 X 1sec, here 1120 w/m2 is the
30
average solar irradiance intensity reaching earth surface during sunny time and 1 sec
is the unit exposure time, otherwise 1.12 kWs/m2) of optical energy is available in
each second to inactivate microbial. This value reduces in a cosine fashion as latitude
increases away from the equator (McGuigan, K.G., et. al 2012).
UVA, and UVB reaching the earth surface plays a major role in optical
inactivation of the bacterial population. This concept is good when applied to zero
turbid water, and can help the sunlight pass through deeper levels of water and can
effectively reduce the bacterial count.
2.6.2.3 Combined Thermal and Optical Inactivation
Inactivation of bacteria by applying both thermal (heat) and optical irradiance
is called combined thermal and optical inactivation. The Combined thermal and
optical inactivation is the mechanism involved in most solar disinfection systems.
These systems help in effective usage of both solar UV and IR for disinfection.
2.6.3
SODIS Systems
Systems that use solar radiation for disinfection are called SODIS systems. These
involve a combination of thermal and optical inactivation of bacteria. Compound
parabolic collector (CPC) reflectors are widely used solar disinfection systems.
Figure 2.3 (Alternative Energy Tutorials) shows the reflection mechanism involved in
compound parabolic collector (CPC) reflectors.
The walls of the CPC act as
reflectors and water containing tube act as a receiver. This has been proven as the
successful solar water disinfection system so far (Mbonimpa E. G. et al. 2012).
Research studies have proven that usage of reflective materials gives better
disinfection rates rather than usage of heat absorbent materials because of the
effective usage of sunlight in both direct (radiation from sun) and indirect (radiation
31
from reflectors) means. The material used for reflecting radiation depends on the
pricing of the material available in market. Researchers are working for developing
the most viable reflection material. Mani, S.K., et. al. 2006 conducted a comparative
study between reactors with reflective, absorptive and transmissive rear surfaces. This
study concluded that reactor with a reflective rear surface performed better in
reducing E. coli than others. Mani, S.K. et al. 2006 conducted some of their studies
in sub-optimal sunlight conditions where thermal effects are minimal and optical
effects is maximized by the return of solar radiation through water under treatment.
This is because of the availability of UVA on cloudy days for reflectors to enhance
the optical inactivation of solar disinfection unlike blackened surfaces that are unable
to raise the temperature of water as required on cloudy days. Figure 2.4 (Plataforma
Solar de Almería, 2006) shows a conventional solar flow reactor unit. This contains
transparent tubes and reflectors. Transparent tubes transmit sunlight through them
and helps in optical inactivation of bacteria.
Reflectors used in this system are
compound parabolic collectors (CPC), which are considered as best reflective shape,
reflect the sunlight and concentrate the reflected light on to the tubes. This helps in
increasing the optical inactivation rate. In addition, the infrared radiation warms up
water and results in thermal inactivation.
32
Figure 2.3 CPC Reflector
Figure 2.4 Conventional Solar Flow reactor
2.7
SODIS Projects Review
PET bottles are the WHO recognized way for solar disinfection in under
developed countries. PET bottles do not transmit UVB, their thin wall thickness
allows them to efficiently transmit 85–90% in the UVA region if the bottles are not
33
old or scratched (McGuigan, K, G. et al 1998). Main concern involved in using
plastic bottles is that they may have the potential to leach compounds into water after
exposure to strong sunlight conditions. However, research results so far show that in
some cases photoproducts such as terephthalate compounds remain on the surface of
the container but do not migrate into water (Wegelin, M. et al. 2001). Carbonyls and
plasticizers are found in water but are well below the limits set for drinking water
quality (Reed, R. H., 2000). SODIS bags maximize the area for photon collection
and minimize the path length for light penetration through water to be treated. Main
drawback in PET bottle SODIS is the low batches they treat. And availability of the
bottles in rural areas and limitations on useful lifetime.
Flow reactors use several reactor designs to enhance solar disinfection and
increase batch size.
Some flow reactors have focused on increasing the optical
inactivation component of sunlight inactivation using solar collectors and reflectors.
Caslake et al. 2004 developed a solar disinfection system based on a PVC circuit
covered by an acrylic layer transparent to the UV range for drinking water
disinfection. The disinfection capacity of this system is 1 liter in 30 minutes, and in
spite of high turbidity, the system obtained a 4-log reduction for total coliforms.
Ubomba-Jaswa et al. 2009 observed that increasing flow rate has a negative effect on
inactivation of bacteria, irrespective of the exposure duration. It seems that at a given
time-point there needs to be maximum exposure of bacteria to UV to ensure complete
inactivation rather than having bacteria repeatedly exposed to sub-lethal doses over a
long period of time. The authors determined that inactivation of bacteria is dependent
on the UV dose rather than UV irradiance. Gill et al. 2010 designed a continuous
flow SODIS reactor capable of delivering 10 L min−1 of treated water and they tested
it in a Kenyan rural village to treat surface waters from a small collection dam. The
34
reactor used 120 m of 47 mm diameter pyrex tubing at the focus of a CPC reflector,
assembled in eight panels. While only preliminary measurements were made soon
after the reactor was completed, these indicated that coliform populations were being
reduced from 102 to 0 CFU/mL after a 20 min single pass residence time. No details
of the cost of manufacture or construction were available.
Polo-López et al.
2011 proposed a continuous single pass flow reactor, which would deliver solar
disinfected water in the outlet of the reactor. This is a sequential batch photo-reactor
which decreased the treatment time required for complete bacterial (E. coli)
inactivation and increased the total output of water treated per day, reducing userdependency. For this, the authors incorporated a CPC reflector of concentration
factor 1.89 which reduced the residence time needed for disinfection and therefore,
treated a higher volume of polluted water in the same time.
The system also
incorporated an electronic UVA sensor which controlled the discharge of the treated
water into a clean reservoir tank following receipt of the pre-defined UVA dose. If
this reactor could be constructed with six modules, it would produce at least 90 L of
potable water per day, and approximately 31,500 L during a typical year. Table 2-1
gives information about the projects that developed SODIS systems and their
capacities. The batch volume given is the amount of water that the system can
disinfect in a single run. The systems given are both dynamic systems in which water
flows continuously through the system and static systems in which water does not
flow and most of the times static systems are PET bottles and bags. Only projects with
information on the volume of water are considered in developing the table. The data
is organized based on the batch volume of water treated, in descending order.
35
Table 2-1 SODIS systems and Their Capacity
Authors
Batch Volume
Title Of The Project
Year
500 Liters
Preliminary Observations Of A Continuous Flow
Solar Disinfection
System For A Rural Community In Kenya
2010
Sommer, B., Marino, A., Solarte, Y., Salas, M. L.,
Dierolf, C., Valiente, C., Wegelin, M.
100 Liters
Sodis An Emerging Water Treatment Process
1997
Anthony Amsberry, Clayton Tyler, William Steinhauff,
Justin Pommerenck, Alexandre T. F. Yokochi
55 Liters
Simple Continuous-Flow Device For Combined
Solar Thermal Pasteurization And Solar
Disinfection For Water Sterilization
2014
Pansonato N, Afonso Mv, Salles Ca, Boncz Ma, Paulo
Pl.
51 Liters
Solar Disinfection For The Post-Treatment Of
Greywater By Means Of A Continuous Flow
Reactor.
2011
A.J. Fjendbo Jorgensen, K. Nohr, H. Sorensen, F.
Boisen
50 Liters
Decontamination Of Drinking Water By Direct
Heating In Solar Panels
1998
L.W. Gill, C. Price
36
O.A.
cloughlina, P. Fern nde Ib e b, W. ernjakb,
S. alato Rodr gue b, .W. illa
37
35 Liters
Photocatalytic Disinfection Of Water Using Low
Cost Compound Parabolic Collectors
2004
Peter Kalt, Cristian Birzer, , Harrison Evans, Anthony
Liew, Mark Padovan, Michael Watchman
34 Liters
A Solar Disinfection Water Treatment System For
Remote Communities
2014
Sadek Igoud, Fatiha Souahi, Chems Eddine Chitour,
Lynda Amrouche, Chahinez Lamaa, Nadia Chekir &
Amar Chouikh
30 Liters
Wastewater Disinfection Using Ultraviolet (Uva,
Uvc) And Solar Radiation
Eunice Ubomba-Jaswa,A, Pilar Fernandez-Ib, Nez,
Christian Navntoft,C
M. Inmaculada Polo-Lopez And Kevin G. Mcguigana
25 Liters
Investigating The Microbial Inactivation
Efficiency Of A 25 L Batch Solar Disinfection
(Sodis) Reactor Enhanced With A Compound
Parabolic Collector (Cpc) For Household Use
2010
M.I. Polo-Lópeza, P. Fernández-Ibáñeza, E. UbombaJaswab, C. Navntoftc, D, I. García-Fernándeza, P.S.M.
Dunlopf, M. Schmidf, J.A. Byrnef, K.G. Mcguigan
25 Liter
Elimination Of Water Pathogens With Solar
Radiation Using An Automated Sequential Batch
Cpc Reactor
2011
R.H. Reed, S.K. Mani, V. Meyer
25 Liters
Solar Photo-Oxidative Disinfection Of Drinking
Water: Preliminary Field Observations
2000
2014
38
P. Fernández-Ibáñeza, C. Sichela, M.I. Polo-Lópeza, M.
De Cara-Garcíab, J.C. Tellob
14 Liters
Photocatalytic Disinfection Of Natural Well Water
Contaminated By Fusarium Solani Using Tio2
Slurry In Solar Cpc Photo-Reactors
2009
P. Fernández, , J. Blanco, C. Sichel, S. Malato
11 Liters
Water Disinfection By Solar Photocatalysis Using
Compound Parabolic Collectors
2005
Takeo S Saitoh, Hamdy H El-Ghetany
8 – 10 Liters
A Pilot Solar Water Disinfecting System:
Performance Analysis And Testing
2002
Takeo S. Saitoh And Hamdy H. El-Ghetany
3 – 5 Liters
A Pilot Solar Water Disinfecting System:
Performance
Analysis And Testing
2001
C. Navntofta, D, E. Ubomba-Jaswab, K.G. Mcguiganb,
P. Fernández-Ibáñezc,
2.5 Liters
Effectiveness Of Solar Disinfection Using Batch
Reactors With Non-Imaging Aluminium Reflectors
Under Real Conditions: Natural Well-Water And
Solar Light
2008
P.S.M. Dunlop, M. Ciavola B, L. Rizzo, J.A. Byrne A
2.5 Liters
Inactivation And Injury Assessment Of Escherichia
Coli During Solar
And Photocatalytic Disinfection In Ldpe Bags
2011
Alejandra Martín-Domíngueza, Ma. Teresa AlarcónHerrerab, Ignacio R. Martín-Domínguezb, Arturo
González-Herrerac
2 Liters
Efficiency In The Disinfection Of Water For Human
Consumption In Rural Communities Using Solar
Radiation
2005
Silvia Gelover, , Luis A. Gómez, Karina Reyes, Ma.
Teresa Leal
2 Liters
A Practical Demonstration Of Water Disinfection
Using Tio2 Films And Sunlight
2006
Laurie F. Caslake, Daniel J. Connolly, Vilas Menon,
Catriona M. Duncanson, Ricardo Rojas, Javad Tavakoli
2 Liters
Disinfection Of Contaminated Water By Using
Solar Irradiation
2004
1.5 Liters
Effect Of Agitation, Turbidity, Aluminium Foil
Reflectors And Container Volume On The
Inactivation Efficiency Of Batch-Process Solar
Disinfectors
2001
1 – 1.5 Liters
Inactivation By Solar Photo-Fenton In Pet Bottles
Of Wild Enteric Bacteria Of Natural Well Water:
Absence Of Re-Growth After One Week Of
Subsequent Storage
2013
1 Liter
Development And Evaluation Of A Reflective Solar
Disinfection Pouch For Treatment Of Drinking
Water
2004
S.C. Kehoe, T.M. Joyce, P. Ibrahim, J.B. Gillespie, R.A.
Shahar, K.G. Mcguigan
39
J. Ndounlaa, E, D. Spuhlerb, S. Kenfackc, J. Wéthéd, C.
Pulgarina,
D. Carey Walker, Soo-Voon Len, Brita Sheehan1
2.8
E. coli
Escherichia coli is a gram-negative, non-spore forming bacillar bacteria which
is a facultative anaerobe and ferments simple sugars like glucose (Unc, A. and Goss,
M. J. 2000). It is a common inhabitant of the intestinal tract of man and other warm
blooded animals. Most of the strains of E. coli live as endo commensals in the
intestinal tract along with other gut-inhabitant bacteria and are harmless. However,
some strains are virulent and cause diarrhoeal illnesses. The four main virulent/
pathogenic
strains
are
enteropathogenic
E.
coli,
enterotoxigenic, E. coli and enterohemorrhagic E. coli.
enteroinvasive
E.
coli,
E.coli being gram-negative
bacteria, produces endotoxins which when released lead to diarrhoeal symptoms.
E. coli is known to be a good biological indicator of water treatment safety for
decades (Edberg, S.C. et al. 2000). The bacterium fulfils several essential conditions
required for an ideal biological indicator. Firstly, it is present in copious amounts in
mammalian (human) fecal matter and also it does not multiply adequately outside the
host. World Health Organization (WHO) states that the presence of fecal bacteria in
drinking water is an important factor in the assessment of water quality. The bacteria
are known to survive in drinking water for over 4-12 weeks depending on several
weather conditions indicated by temperature, pH, microflora and others. Studies have
reported that E. coli can be expected to survive in the river water for approximately 30
days. This is a huge advantage as a cost effective protocol can be used. After testing
several other enterogenic bacteria, it has been suggested by several studies that E. coli
is a single best biological indicator. The methods available for the detection of E. coli
are sensitive (sensitivity in testing is perfect identification of the required bacteria
without any influence of other bacteria present in the sample); inexpensive (some
40
detection techniques require lots of infrastructure when compared to others, an
inexpensive method can save money and resources); specific (specificity is defined as
the identification of a required or particular strain of bacteria in a bacterial group (for
example: there are testing procedures for finding out the E. coli O157:H7, which are
present in low concentrations) and less technique sensitive (this is reduction of
standard operation procedural steps involved in analyzing a sample for bacteria. This
saves time.).
E. coli contamination poses a huge threat to the safety of drinking water. The
presence of E. coli in drinking water is considered unsafe. This occurs by the fecal
contamination of humans or animals into water resources. Studies have demonstrated
that public health threat comes from sewage intrusion, which is expected to have high
concentration of E. coli (108-109 colonies/100ml). Many studies have signified E.
coli had higher or at least equal survival rate to several other bacteria on disinfection.
As stated by WHO, that water contamination should be tested often to avoid
water borne diseases, therefore, the method to detect the contamination should be
sensitive yet economical and accessible. Although several other bacteria have been
tested for biological indicators of safe drinking water like Enterococci, Clostridium
perfringens, somatic phages etc.
However, E. coli still stands above all in its
application as a biological indicator due to the presence of simple methods. Methods
that involve testing E. coli concentration in water range from qualitative analysis to
quantitative analysis.
2.8.1
Qualitative Analysis of water for E. coli
This analysis used as verification means to indicate whether there is any E.
coli contamination in the collected samples or not. There are many onsite, home
41
based water analysis kits for qualitative analysis of bacteria. H2S paper strip method
is the most used or tested for its performance, because of its implementation and
pricing. Pillai, J. et al 1999 proved that H2S paper strip method is the most reliable
method for qualitative analysis for fecal coliforms and this method do not require
access to incubators, freezers and other lab equipment that used for testing fecal
coliform presence in water samples.
This method can be performed at room
temperatures. Manja et al., (1982) developed this on-site microbial water testing
method. H2S paper strip method works based on the detection of hydrogen sulphide
producing bacteria, and there are high concentrations of sulphate reducing bacteria
that are present in human faeces. The method is less expensive, and can give a faster
result.
Previous research studies (Grant, and Ziel, 1996; Hewison et al., 1988;
Sivaborvorn, and Dutka, 1989) show that this method do not required technical
personnel to conduct it and have a good correlation with the standard methods. Pillai,
J et al. 1999 conducted this method at different temperatures and concluded that this
procedures work better between temperatures 20 – 440C. Research study conducted
by Anwar, M. S, et al. 1998 in Pakistan proved that H2S paper strip method is a good
qualitative indicator test for fecal coliform. Wright, J. A. et. al., 2012 compared
alternative methods for bacterial analysis and concluded that H2S is best available
onsite method based on accuracy, pricing and implementation.
2.8.2
Quantitative analysis of water for E. coli
This analysis gives the number of bacterial colony forming units (CFU)
present in water samples. CFU is defined as the rough estimate of the number of
viable bacteria or fungal cells in a sample, who have an ability to multiply via binary
fission under the controlled conditions. There are many methods available for
analyzing the E. coli concentration in water samples. EPA (United States of America
42
Environmental Protection Agency) has approved ten enzyme-based total coliform and
E. coli detection tests for examination of drinking water (Olstadt, J. S., et al., 2007).
They are, Colilertw, Colilert-18w, Colisurew, m-Coli Blue 24w, Readycultw
Coliforms 100, Chromocultw, Coliscanw, E p Colitew, ColitagY and MI Agar. All
these tests detect the en ymes β-D galactosidase and β-D glucuronidase which are
uniquely associated with total coliforms and E. coli, respectively. This includes
addition of buffers, salts and micro-nutrients to enhance enzyme expression.
Antibiotics are added to suppress the activity of non-coliforms. MI Agar, an EPA
suggested technique is used for quantitative analysis of water samples in this project
2.8.2.1 MI Agar method
EPA suggested method (Method 1604, EPA) MI Agar method is a
combination of media and membrane filtration. This method gives the Total Coliform
and E. coli concentrations in the samples. The substrates involved with this method
are MUGal (4-methylumbelliferyl-ß-D-galactopyranoside) for detection of total
coliform and IBDG (Indoxyl-ß-D-glucuronide) for detection of E. coli (Olstadt, J et
al., 2007).
MI agar medium in form of powder are available and the plating procedure
involves addition of 36.5 gms of MI agar to 1000 ml of double distilled water and
autoclaved for 15 minutes at 1210C at 15lb pressure. Then the solution is transferred
to water-bath maintained at 500C for tempering agar. A 5ml of antibiotic Cefsulodin
solution (concentration of 1mg/ml) is filtered through a 0.22 µm pore size, 25mm
diameter sterile syringe filter. This filtered antibiotic is then added to the agar right
before pouring of plates. The plates are then allowed for settling down. Once settled
43
plates are tested for any bacterial growth in them. The plates with any bacterial
growth must be discarded and the rest should be stored at 40C for usage.
An appropriate volume of a water sample (10, 25, 50 or 100 ml) is filtered
through a 47-mm, 0.45-µm (The size of fecal coliforms is between 0.5 to 2 µm in
diameter and 1 to 4 µm in length, Unc, A. and Goss, M. J. 2000) pore size cellulose
ester membrane filter that retains the bacteria present in the sample (Method 1604,
EPA). Then the filter is placed on the plate of MI agar and the plate is incubated at
35°C for up to 24 hours. The blue colour bacterial colonies that grow on the plate are
E. coli and colonies that are fluorescent under long-wave ultraviolet light (366 nm)
are total coliforms other than E. coli. When water sample used is not 100 ml,
equation 2.4 gives the estimation of E. coli concentration in 100 ml.
(
)
(2.4)
Where,
NBC = Number of blue colonies
V = Volume of water sample (ml)
Equation 2.5 gives the total coliforms (TC) in water sample.
(
TC = Total Coliforms
NBC = Number of blue colonies
NFC = Number of fluorescent colonies
V = Volume of water samples (ml)
44
)
(2.5)
2.9
Project Significance
From the previous discussions about past research projects, it can be concluded
that UVB or UVA, along with infrared radiation plays a significant role in water
disinfection by using solar irradiance. This happens because of optical inactivation
and thermal inactivation. In most of the cases the material (transparent pipes) used
for exposing water to sunlight either filters UVA or UVB in the solar spectrum, but
increases water temperature. Unlike these previous projects, this project adopts the
open channel flow concept to test the effective ness of UVB and UVA radiations in
bacterial inactivation.
temperature
never
Effect of infrared radiation was not significant, as water
exceeded
the
thermal
45
inactivation
threshold
of
380C.
3 MATERIALS AND METHODS
3.1
Introduction
All materials to construct and methods for developing the project are discussed
in this chapter. Effort was taken to keep this project as sustainable as possible by
using solar panels for generating electricity, non-chemical disinfection of water, and
gravitational circulation of water throughout the system. Following sections will give
a clear picture of the components used in this project and methods implemented in
this. The raw water for this project is drawn from Beargrass Creek, an urban stream
in Louisville metro area because of high bacterial concentration in water. The reason
behind using this water as raw water is explained in detail.
3.2
Project Setup
The pilot water treatment project have four components:
1. Pumping water into storage tank
a. Photo voltaic (PV) panels
b. Solar powered submersible pump
2. Filtration
a. Sand
b. Gravel
c. Activated charcoal
d. Crushed oyster shells
3. Disinfection
46
a. Solar radiation
4. Aeration
a. Water fall
No chemicals or fossil fuels were used in this system. Major portion of
materials were bought local or in 500miles radius. Figure 3.1 shows the project setup.
Solar panels are to power the pump for pumping water in to water tank. The four
filters are for water filtration, filled with different filter material. SODIS troughs are
for exposing water to sunlight. Overflow from tank takes out the surplus water from
tank and this water flows back into the stream through water fall for increasing the
dissolved oxygen (DO) concentration in water.
Water Tank
Overflow from Tank
Solar Panels
Filters
Water Fall
SODIS Troughs
Figure 3.1 Project Setup
3.2.1
Water Pump, PV Panels, and Storage Tank
Six solar panels are installed to power the submersible pump that is installed
in the creek. This pump pumps water into a storage tank that is about 35 feet above
47
water level in the creek. The over flow water flows back into the creek through a
concrete water fall, this water fall creates ripple effect and helps in increasing the
Dissolved Oxygen (DO) concentration in water. The storage tank helps in reducing
settling down the sediment in water. Figure 3.2 shows the PV panels setup for
powering the pump.
Figure 3.2 Panels for Powering Water Pump
3.2.2
Filtration
American Water Works Association’s manual of design of slow sand filtration
was followed in designing slow sand filters.
Filters are designed to reduce the
suspended solids in water for increased penetration of sunlight into water.
Mechanism involved in setting up a filter is using coarser material in the bottom and
gradually decreasing the grain size to finer material in the top.
This helps in
controlling the finer particles entering into the plumbing and clogging them
(Hendricks, D., et al., 1992).
48
3.2.2.1 Sand
Sand filters are good in reducing the suspended particles and bacterial
concentrations in water over the course of time because of the development of a
biofilm called Schmutzdecke in the top few millimetres of the fine sand layer.
Schmutzdecke is formed in the few days of filter operation depending on the flow into
the filters and consists of different species ranging from bacteria to protozoa
(Huisman, L 1974). A fine particulate sand is used in this pilot study to reduce as
much of total suspended solids (TSS) as possible.
3.2.2.2 Oyster Shells
Oyster shells, because of the rich calcium content in them are being used as
the calcium supplement in chicken industry. In addition, they are good in reducing
the NH3-N (Ammonical nitrogen) concentrations in water (Liuin, Yao-Xing 2010).
Commercially available crushed oyster shells because of their size can also be used as
a coarser particle in the filter eliminating a portion of gravel used in filters. Gravel in
filters do not have any significance in water purification (Collins, M. R 1998).
Replacing a portion of gravel with some material of similar particle size and a better
water treating agent can help in improving the filter performance.
But total
replacement of gravel with Oyster shells can’t be a better option because it takes long
time to dissolve a pebble than an oyster shell. Crushed oyster shells can best fit in this
zone because of three reasons 1) Particle size similar to gravel; 2) Price, a 50lbs bag
of shells costs only $10; 3) They are proven as good reducing agents of NH3-N
compounds in water and also performs better if pre-processed in reducing Total
Phosphorus concentrations in water (Liuin, Yao-Xing 2010).
49
3.2.2.3 Activated Charcoal
Activated charcoal has been used as a filter material for increasing odour and
taste of the potable water (EPA). The mechanism involved in activated charcoal
filtrating is adsorption, because of its high porosity and provides large surface area to
which contaminants may absorb. Granular activated charcoal, derived from burning
of coconut shells is used in this project. In the beginning, activated charcoal was used
as a filter for adsorbing wide range of chemicals (EPA). However, research studies
show that it can effectively adsorb E. coli bacteria depending on the retention time
(Katsumi, N 2000). In addition, their particle size makes it as a perfect match to be
applied in the filter in between coarse to finer material.
A 1 foot diameter 20 feet long schedule 80 PVC pipe was cut into four 5 feet
long pipes and are filled with filter materials in different proportions. Table 3-1
shows the filter specifications. Figure 3.3 shows the Filter arrangement. Figure 3.4
show the inflow controls into filters. Figure 3.5 shows the outflow control from the
filters and inflow into the solar troughs. Water flow is gravitational into the filters
and controlled individually at the inflow of each filter.
Table 3-1 Filter Specifications
Filter
Filter Media
1
Gravel – 11”; Oyster Shells – 7”; Sand – 3.5”
2
Gravel – 11”; Oyster Shells – 6” Activated Charcoal – 3.5”
3
ravel – 11”; Activated Charcoal – 7”
4
ravel – 11”; Oyster Shells – 7”
50
Figure 3.3 Filter Arrangement Showing Inflow and Outflow Controls
Figure 3.4 Inflow Control into Filters
Figure 3.5 Outflow Control from Filters
51
3.2.3
CPC reflector systems collect and illuminate the pipe in regular SODIS
applications. The pipes used are transparent, and these materials range from Pyrex,
polyethylene, acrylic... etc.
ost of these materials don’t transmit 100% of the UV
radiation from sun. Moreover, because of the closed system, oxygen levels may not
be raised. Circular shape of the pipes will have a minimal area of exposure to direct
sunlight.
Caslake et al.
2004 developed a system with semi-circular exposure
surface. The system used is serpentine shape grooved on a PVC sheet and is covered
by acrylic layer. This system has successfully obtained a 4-log reduction in spite of
high turbidity. However, it is a small system, which has a capacity of 1 litre. Most of
the projects apply the combination of Thermal and optical inactivation of bacteria by
sunlight. In addition, majority of studies have concentrated on UVB radiation in
sunlight for disinfection.
Few studies have concentrated on UVA radiation for
disinfection. UVA is also proven as a potential disinfecting radiation. There are
limited number of studies addressed the effectiveness of both radiations in
disinfection that is optical inactivation.
This project studies the effectiveness of solar radiation in just optical
inactivation of bacteria. For that, this project adopted the open channel concept.
Infrared radiation of solar radiation helps in increasing the temperatures and when
water temperatures reaches 500 C disinfection rate reaches maximum and that
situation will reduce the choice of studying only optical inactivation process. Open
channel also helped in to achieve the maximum water surface exposure to sunlight.
Open channel helps in increasing oxygen levels and when hit by UV transforms into
ROS and increases the disinfection rate.
The introduction of different filtration
materials help in reducing the TSS, nutrient levels in water and reduces the load on
52
UV chamber. Reduction of nutrient levels help in cutting down the food chain to
bacteria. This project used the fundamental expressions in hydraulics and SODIS at
design phase and system is altered over the course of time depending on the
performance.
In this study, 18-inch pvc pipes are cut into half to create semi-circular
channels. Equation 3.1 below defines removal percentage of Escherichia coli (E. coli)
(cdc.gov/ecoli) from water using a first-order decay relation. Simulated results with
exposure time required for 10 percent to 99.9 percent removal of E. coli over a ten
percent increment is presented in Table 3-2.
(3.1)
N - Final E. coli concentration (CFU/ml)
N0 - Initial E. coli concentration (CFU/ml)
Ki - Inactivation rate constant (cm2/(µW min))
I - Intensity of solar radiation (µW/cm2)
T - Time of exposure (min)
I - 94 (average of solar irradiance) for Louisville area (ref: http://www.nrel.gov)
Table 3-2 Exposure time summary
% Removal
N/N0
K
99.9
0.001
0.03
90
0.1
0.03
80
0.2
0.03
70
0.3
0.03
60
0.4
0.03
50
0.5
0.03
40
0.6
0.03
30
0.7
0.03
20
0.8
0.03
10
0.9
0.03
hrs = hours; mins. = minutes
F = I*T
I
T (hrs)
T (mins.)
230.25
76.75
53.64
40.13
30.54
23.10
17.02
11.88
7.43
3.51
94
94
94
94
94
94
94
94
94
94
2.44
0.81
0.57
0.42
0.32
0.24
0.18
0.12
0.08
0.04
146.97
48.99
34.24
25.61
19.49
14.74
10.86
7.58
4.74
2.24
53
A simulation was carried out using controlled flow values of 75, 85 and 100
gallons/hour was used to estimate flow travel length required to achieve exposure
duration for disinfection. Those results are presented in table 3-3. Exposure time and
flow area are constant and velocity varies with respect to the flows and with flow
lengths. Equations 3.2, 3.3 and 3.4 define flow velocity (V), wetted area (A) of a
horizontal cylinder and flow length (L), respectively,
(3.2)
V = Velocity of flow (feet/hour, meter/hour)
A = Wetted area of the horizontal cylinder (feet2)
(
)
(
)√
(3.3)
r = radius of the cylinder (inches)
h = water depth or wetted depth (inches)
Q = Volumetric flow rate (gallon/hour (gph) = 0.134 ft3/hour = 3.785 liter/hr (lph))
L = Flow length (inches)
( )( )
54
(3.4)
Table 3-3 Flow lengths from volume flow values
Q = 75
75 gph
283.91 lph
Velocity
6.36 fph
Exposure
Time
(mins.)
146.97
48.99
34.24
25.61
19.49
14.74
10.86
7.58
4.74
2.24
1.94 m/h
Flow Length
feet
15.50
5.17
3.61
2.70
2.06
1.56
1.15
0.80
0.50
0.24
meters
4.73
1.58
1.10
0.82
0.63
0.48
0.35
0.24
0.15
0.07
Q = 85
85 gph
321.76 lph
Velocity
7.18 fph
4.31 m/h
Flow Length
feet
17.50
5.83
4.07
3.05
2.32
1.75
1.29
0.90
0.56
0.26
meters
5.34
1.78
1.24
0.93
0.71
0.53
0.39
0.27
0.17
0.08
Q = 100
100 gph
378.54 lph
Velocity
8.45 fph
5.07 m/h
Flow Length
feet
20.59
6.86
4.79
3.58
2.73
2.06
1.52
1.06
0.66
0.31
meters
6.28
2.09
1.46
1.09
0.83
0.63
0.46
0.32
0.20
0.09
gph = gallons/hour; lph = liters/hour; fph = feet/hour; m/h = meters/hour
3.3
Construction
Two 18” X 10 feet long pvc pipes are cut into two half cylinders with
rectangular base and semi-circular ends. Each half cylinder is painted with different
colour either with reflective paint or with heat absorbing paint. Figure 3.6 shows the
semi-circular troughs painted in different colours. Water flowing out of the filters
flows into separate troughs and filled up to the designed depth. Water then flows out
by opening the valve shown in figure 3.6a. Table 3-4 gives details about the painted
surfaces and why they are applied.
55
Table 3-4 Painted Troughs
Trough
Paint
Purpose
1
White
Best reflector, Cheap reflecting agent
2
Spray Painted Aluminum
Finish
Better reflector than White but expensive
3
None
Left unpainted for control
4
Black
Absorbs more heat than other materials
Figure 3.6 SODIS Troughs Setup and Out Flow Control
Figure 3.6 a Trough out Flow Valve
56
3.4
Operation
The pilot project is operated in two phases with respect to flow. Phase I is a
static batch system. In which troughs were filled and allowed water to expose to
sunlight for 2 hours. Each trough is capable of holding 113 gallons with a water
depth of 8”. Phase II is a continuous flow system in which water flow is continuous
into the troughs at a constant flow rate and the event ends with water reaching
targeted depth in targeted time. Two flow depths are tested at three different targeted
times.
Scenario I
Water flowing out of filters is made to achieve 8” depth over the period of 3.5
hours (113 gallons in 3.5 hrs). But the trough painted white that is attached to the
filter 1 can’t attain the desired flow depth because of the fine grained sand used in the
filter created low pore size and not allowed water pass through as the other filters.
Trough 1 is able to attain the desired flow depth of 8” in 6.0 hrs. Flow rate input into
water for this is 32.3 gal/hr.
Scenario II
Water flowing out of filters is made to achieve 8” depth over the period of 6.0
hours (113 gallons in 6.0 hrs). In this case, trough painted white is able to attain the
targeted depth of 8” in 6.0 hrs. Flow rate input into water for this is 18.8 gal/hr.
Scenario III
Water flowing out of filters is made to achieve 3.5” depth over the period of
5.0 hours (36.15 gallons in 5.0 hrs). Flow rate input into water for this is 7.3 gal/hr.
57
All flows are measured using a measure jar of known volume over time. Each
flow is measured up to 5 times and averaged. Calibration continued until averaged
flow values are equal to the desired flow rate.
3.5
Raw Water for Experiments
The raw water for this project is water drawn from the Beargrass creek. Water
drawn from a natural source is due to the presence of organic and inorganic matter
present in water during disinfection has an important effect on both the kinetics and
the final disinfection result (McGuigan, K.G 2012). Using a natural source of water
gives a better prediction of microbial inactivation under real conditions.
Using
natural water avoids weakening of bacterial cells due to an unfavourable osmotic
environment (lack of ions).
3.6
3.6.1
Sampling and Testing
Sample Collection
Water samples for microbial testing were collected by following grab
sampling. Samples are collected using 150 ml bottles with leak proof lids. Sample
containers were opened just before taking water sample. Inside of the containers was
never touched.
Sample containers were never reused.
Containers with sodium
thiosulfate tablets were used to reduce the chlorine concentration in water if present.
Samples were stored in ice bag without immersing them into the ice. A temperature
of 1-4°C was maintained during transit to the laboratory. It used to take around 30-45
mins to reach the lab and start the analysis. Figures 3.7 and 3.8 show water sample
collection bottle and cooler bag for transporting water samples to lab. Care was taken
that the sample bottles never sunk into the ice. Water samples for physical parameter
analysis was done at the site by using the probes. Analysis of water in troughs is done
58
by introducing the probe in water. Water sample analysis for water coming out of
tank and filters are collected in water sample collection bottle and probes are
introduced into the bottle.
Figure 3.7 Sampling Bottles Closed, Opened and Labelled
Figure 3.8 Cooler Bag for Transporting Water Samples
59
3.6.2
Microbial Analysis
EPA’s
ethod 1604 was used for conducting the quantitative analysis of E.
coli in water. This method uses the MI agar medium for growing colonies. A known
volume of water sample (10, 25, 50ml) is diluted with double distilled water and is
filtered through a 0.45µm filter membrane. Figures 3.9 and 3.10 show the 0.45 µm
cellulose ester membrane filter and the filtration system.
Then the membrane is
plated on the MI agar medium. Figure 3.11 shows an example of the plate loaded
with the membrane and the plates are incubated at 350 C for 24 hours. The plates are
then taken out of the incubator and colonies are counted manually. Figure 3.12 shows
an example of the incubated plate with bacterial growth on it. The results were then
expressed in colonies/100ml using the equation 3.5 Bacterial change at different
stages are analysed and bacterial reduction is calculated on percentage and
logarithmic scales.
(3.5)
60
Figure 3.9 0.45 µm Pore Size Cellulose Ester Membrane
Figure 3.10 Filtration Assembly
61
Figure 3.11 Plate Loaded with the Membrane
Figure 3.12 Incubated Plates with Bacterial Growth
3.6.3
Physical Water Analysis
Water samples are analysed for pH, temperature, Dissolved Oxygen (DO), and
conductivity using the probes “Extech DO610 ExStik II DO/pH Conductivity Kit”.
62
Figure 3.13 shows the probes used for sampling. Stream water parameter values are
downloaded from USGS website. Stream water quality data is downloaded from
USGS website (USGS water quality data).
Figure 3.13 Extech DO610 ExStik II DO/pH Conductivity Kit
3.7
Meteorological Data
Meteorological data accessed for this project is, solar irradiance (watts/m2), air
temperature (0C or 0F), previous hour precipitation (inches, or cms), humidity (%),
solar azimuth angle (in degrees), and cloud cover (%).
The hourly data of the above parameters is bought from the weather analytics
website. All the data provided for a Weather Analytics station comes from the
Climate Forecast System Reanalysis (CFSR) data set. The CFSR data set was created
by The National Centres for Environmental Prediction (NCEP). The CFSR data set
was constructed with the combination of a full atmospheric model, satellite
63
observations, upper air balloon observations, aircraft observations and ground
observations (Weather Anlytics website). This data is collected from the sensors
installed at Standiford field, Louisville international airport, which is 5.65 miles (9.09
km) from the pilot project site (straight line). Figure 3.14 shows the straight-line
distance between the pilot project site and Standiford field.
Figure
3.14
Straight
Line
Distance
64
between
SDF
and
Beargrass
Falls
4 METEOROLOGICAL DATA
4.1
Introduction
This chapter gives detailed information about the measurement of solar
radiation reaching earth’s surface. Factors that affect solar radiation and effects of
solar radiation on temperature variations during a day are discussed. Discussion is
done by using the past research and the graphical illustration of the discussion is done
by using the data acquired for this project from the weather analytics website. Data
chosen for this discussion is the average of the data values between sunrise and sun
set times in a day is considered as daily average. The data used for analysis is from
weather analytics. Weather Analytics uses the meteorological data from the groundinstalled stations
4.2
Solar Radiation Measurement
The electromagnetic radiation emitted by sun is called solar radiation.
Extraterrestrial radiation (ETR) is the amount of solar radiation at the top of the
earth’s atmosphere. Earth revolves around the sun in an elliptical orbit and this result
in the variation of distance between Earth and Sun. This affects the amount of solar
radiation reaching Earth’s outer atmosphere. The ETR value varies between 1412
W/m2 and 1321 W/m2 (Paulescu, M. et al. 2013). Measurement of solar irradiation
at Earth’s surface is done in different ways.
Three commonly measured solar
radiation quantities are: direct normal or beam irradiance; diffuse horizontal
irradiance;
global
horizontal
65
irradiance.
4.2.1
Direct Normal or Beam Irradiance
Direct normal irradiance (DNI) is the amount of the solar radiation from the
direction of the sun. This is measured in the surface that is held perpendicular to the
straight line from the direction of sun.
4.2.2
Diffuse Horizontal Irradiance
Diffuse horizontal irradiance (DHI) is defined as the amount of radiation
received per unit area on earth’s surface that has been scattered by molecules and
particles. The absence of atmosphere results in no diffuse radiation recorded.
4.2.3
Global Horizontal Irradiance
Global horizontal irradiance (GHI) is the sum of direct normal irradiance,
diffuse horizontal irradiance, and ground-reflected radiation.
radiation is insignificant compared to DHI, and DNI.
Ground reflected
Therefore, excluding the
ground reflected radiation DHI and DNI are considered for calculating GHI.
Equation 4.1 gives the estimation of GHI.
(
)
(4.1)
Figure 4.1 shows the GHI, DHI, and DNI measurements (Texas State Energy
Conservation office, 2008).
66
Figure 4.1 Measurement of GHI, DHI, and DNI
Solar zenith angle is the angle between the sun and the overhead point of the
location where the irradiation. This angle is useful in determining the sunrise and
sunset. Figure 4.2 (City University of New York 2013) shows the solar azimuth angle
measurement.
Figure 4.2 Solar Zenith Angle
4.3
Seasonal Variations of the Solar Radiation
Seasons are caused because of the tilt of earth on its axis. This controls the
daylight length and solar irradiance reaching earth surface. Figure 4.3 (National
Oceanic and Atmospheric Administration, NOAA) shows the tilted earth’s elliptical
67
orbit around the sun and cause of seasons. Duration of sunlight in summer is more
than other seasons and the intensity is high because of the earth’s tilt towards the sun.
Figure 4.4 shows the chart developed for average solar irradiance during the second
and first full months of spring (April), summer (July), fall (September), and winter
(January) in Louisville.
Meteorological data used to develop the chart is from
weather analytics website. This website acquire the data from the weather station
installed at Louisville international airport. This chart shows that solar radiation
reaching earth’s surface is high in summer and low in winter.
Figure 4.3 Earth’s Tilt Cause of Season
68
Seasonal Variation of Solar Radiation (W/m2)
500
Solar Raditaion (W/m2)
450
400
350
300
250
200
150
100
50
0
January (Winter)
April (Spring)
July (Summer)
Septemebr (Fall)
Season
Figure 4.4 Seasonal Variation of Solar Radiation
4.4
Hourly Variations of Solar Radiation during the Day
Sunrise and sunset times varies based on the seasons. This occurs because of
the earth’s tilt. The variation of solar radiation during the day is due to the change of
the solar zenith angle. Figure 4.5 (International network for sustainable energy,
INFORSE) shows the seasonal variation of path of sun for the months June,
December, March, and September. This shows the path of sun as nearest during
month of June. This is the basic reason for summer. Figure 4.6 (INFORSE) shows
the solar path during a day. The position of sun over the zenith during mid-day is the
reason for maximum solar radiation reaching earth’s surface.
69
Figure 4.5 Seasonal Path of Sun
Figure 4.6 Hourly Path of Sun
Table 4-1 shows the hourly solar radiation values during a day at Louisville.
Days selected are the starting days of seasons. The location of the weather measuring
station is at Louisville airport whose latitude and longitude are 38.244 and -85.625.
Whereas the latitude and longitude of the project site are 38.260 and -85.71. Figure
4.7 shows the chart developed showing the seasonal hourly variations of solar
70
radiations in a day. This chart shows the maximum solar radiation between 1:00 pm
an 4:00 pm and the zero value shows the solar radiation value before sunrise or after
sunset. Whereas, there is a dissimilarity for fall season (2013-09-21) because of the
high cloud cover recorded on that day. To demonstrate the relationship more clearly
for fall season figure 4.8 is developed for the second day of fall season (2013-09-22)
on which the cloud cover is minimal to zero. The effects of cloud cover on solar
radiation is explained in cloud cover section.
71
Table 4-1 Seasonal Hourly Solar Radiation at Louisville
Hour
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
Fall 2013
09-21
09-22
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
24
122
89
323
276
516
417
671
468
776
503
815
517
797
696
698
523
527
330
325
129
128
0
0
0
0
0
0
0
0
0
0
Solar Radiation (W/m2)
2013-12-21
2014-03-21
(Winter)
(Spring)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
79
8
281
27
436
13
612
8
714
13
738
24
672
41
390
39
301
18
198
0
94
0
0
0
0
0
0
0
0
0
0
72
2014-06-21
(Summer)
0
0
0
0
0
0
10
118
292
460
582
715
806
831
790
639
491
355
224
110
10
0
0
0
Hourly Variation of Solar Radiation in Four Seasons
900
Solar Radaiton (W/m2)
800
700
600
500
400
300
200
100
0
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Hours
2013-09-21 (Fall)
2013-12-21 (Winter)
2014-03-21 (Spring)
2014-06-21 (Summer)
Figure 4.7 Hourly Variation of Solar Radiation on First Days of 4 Seasons
Hourly Variation of Solar Radiation on Second Day of Fall
900
800
700
600
500
400
300
200
100
0
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Hours
Solar Radiation
Figure 4.8 Hourly Variation of Solar Radiation on Second Day of Fall 2013
73
4.5
Cloud Cover
Cloud cover is the most important factor affecting the solar radiation reaching
earth’s surface. Amount of cloud cover is inversely proportional to the solar radiation
reaching earth’s surface. Cloud cover is measured in percentage and is measured by
human observations. Table 4-3 shows the cloud cover (CC) and solar radiation (SIR)
values for the start days of the seasons. Figures 4.9, 4.11, 4.12, and 4.13 are the
charts showing the relationship between solar radiation and cloud cover during fall,
winter, spring and summer. Figure 4.10 shows the chart developed for the second of
fall 2013 to demonstrate the inverse relationship of solar radiation and cloud cover
more clearly.
74
Table 4-2 Cloud Cover and Solar Radiation on First Days of Seasons
Fall
Hour
2013-09-21
2
75
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
2013-12-21 (Winter)
2014-03-21 (Spring)
2014-06-21 (Summer)
2013-09-22
2
SIR (W/m )
CC (%)
SIR (W/m )
CC (%)
0
0
0
0
0
0
0
0
24
89
276
417
468
503
517
696
523
330
129
0
0
0
0
0
100
100
100
100
100
100
100
100
100
100
98
90
77
3
3
2
2
2
2
3
1
1
2
1
0
0
0
0
0
0
0
0
122
323
516
671
776
815
797
698
527
325
128
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
SIR (W/m2)
CC (%)
SIR (W/m2)
CC (%)
SIR (W/m2)
CC (%)
0
0
0
0
0
0
0
0
0
8
27
13
8
13
24
41
39
18
0
0
0
0
0
0
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
0
0
0
0
0
0
0
0
79
281
436
612
714
738
672
390
301
198
94
0
0
0
0
0
0
1
3
4
4
6
12
56
53
36
31
31
38
96
97
96
92
90
88
87
91
91
88
80
0
0
0
0
0
0
10
118
292
460
582
715
806
831
790
639
491
355
224
110
10
0
0
0
92
59
61
60
60
57
57
66
68
61
56
54
55
69
79
84
87
89
91
96
83
86
83
82
900
800
700
600
500
400
300
200
100
0
100
90
80
70
60
50
40
30
20
10
0
Cloud Cover (%)
Solar Radiation and Cloud Cover Relation (Fall)
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Hour
Solar Radiation
Cloud Cover
Figure 4.9 Hourly Relation of Solar Radiation and Cloud Cover in Fall (09 -21-2013)
Solar Radiation and Cloud Cover Relation (Fall)
100
800
700
80
600
500
60
400
40
300
200
Cloud Cover (%)
900
20
100
0
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour
Cloud Cover (%)
Figure 4.10 Hourly Relation of Solar Radiation and Cloud Cover in Fall (09 -22-2013)
76
900
100
90
80
70
60
50
40
30
20
10
0
800
700
600
500
400
300
200
100
0
Cloud Cover (%)
Solar Radiation and Cloud Cover Relation (Winter)
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Hour
Solar Radiation
Cloud Cover
Figure 4.11 Hourly Relation of Solar Radiation and Cloud Cover in Winter (12 -21-2013)
Solar Radiation and Cloud Cover Relation (Spring)
900
700
80
600
500
60
400
40
300
200
Cloud Cover (%)
100
800
20
100
0
0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Hour
Solar Radiation
Cloud Cover
Figure 4.12 Hourly Relation of Solar Radiation and Cloud Cover in Spring (03 -21-2014)
77
Solar Radiation and Cloud Cover Relation (Summer)
900
100
700
80
600
500
60
400
40
300
200
Cloud Cover (%)
800
20
100
0
0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Hour
Solar Radiation
Cloud Cover (%)
Figure 4.13 Hourly Relation of Solar Radiation and Cloud Cover in Summer (06 -21-2014)
Temperature and Solar Radiation
Temperature is directly proportional to solar radiation. Temperature decreases
with decrease in the solar radiation. Table 4-3 shows the hourly temperature and solar
radiation values on the starting days of fall, winter, spring, and summer. Figures 4.14,
4.15, 4.16, and 4.17 shows the relation between hourly solar radiation and
temperature.
78
Table 4-3 Hourly Variations of Temperature and Solar Radiation
0
2013-09-21
(Fall)
Tem
SIR
p (F) (W/m2)
68
0
1
65.9
0
61.5
0
43.5
0
70.3
0
2
3
65
63.7
0
0
61.1
60.4
0
0
42.5
41.7
0
0
69.3
67.7
0
0
4
5
62.4
61
0
0
60.5
61
0
0
40.7
40
0
0
67.6
69.1
0
0
6
59.3
0
61.7
0
39.9
0
72
10
7
8
59.7
59.3
0
24
60.2
61
0
0
44.5
49.9
0
79
75.2
79.4
118
292
9
10
11
12
61.1
66.1
70.1
72.4
89
276
417
468
61.5
61.8
62.4
63
8
27
13
8
54.3
58.6
61.4
63.2
281
436
612
714
83.2
85.5
87.2
88.6
460
582
715
806
13
72.2
503
62.7
13
66.5
738
89.9
831
14
15
72.6
72.1
517
696
64.2
65.2
24
41
66
65.1
672
390
89.7
88.7
790
639
16
17
70.5
66.2
523
330
65
65
39
18
62.9
58.7
301
198
87.3
85.2
491
355
18
19
59.6
58.8
129
0
65.4
65.8
0
0
54.3
54.5
94
0
80.5
71.1
224
110
20
21
22
56.7
54.7
54.3
0
0
0
66.6
67.7
67.4
0
0
0
53.4
52.1
51.7
0
0
0
66.1
65.8
65.3
10
0
0
23
53.8
0
66.6
0
51.3
0
66.5
0
Hours
2013-12-21
(Winter)
Temp
SIR
(F)
(W/m2)
60.2
0
79
2014-03-21
(Spring)
Temp
SIR
(F)
(W/m2)
41.9
0
2014-06-21
(Summer)
Temp
SIR
(F)
(W/m2)
68.2
0
900
90
800
80
700
Temperature (F)
100
70
600
60
500
50
400
40
300
30
20
200
10
100
0
Hourly Variation of Solar Radiation and
Temperature (Fall)
0
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Hours
Temperature (F)
Figure 4.14 Hourly Variations of Temperature and Solar Radiation in Fall
100
900
90
800
80
700
70
600
60
500
50
400
40
300
30
20
200
10
100
0
0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Hours
Temperature (F)
Figure 4.15 Hourly Variations of Temperature and Solar Radiation in Winter
80
Temperature (F)
Temperature (Winter)
100
900
90
800
80
700
70
600
60
500
50
400
40
300
30
20
200
10
100
0
Temperature (F)
Hourly Variation of Solar Radiation and Temperature
(Spring)
0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Hours
Temperature (F)
Figure 4.16 Hourly Variations of Temperature and Solar Radiation in Spring
100
900
90
800
80
700
70
600
60
500
50
400
40
300
30
20
200
10
100
0
0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Hours
Temperature (F)
Figure 4.17 Hourly Variations of Temperature and Solar Radiation in Summer
81
Temperature (F)
Temperature (Summer)
Conclusion
From the above data and results it is learnt that the solar radiation reaching
earth surface at a given time is dependent on the season, time of the day, and cloud
cover at that time. Temperature increases with increase in solar radiation. For SODIS
solar radiation and temperature are important factors. In addition, temperature is
dependent on solar radiation. Therefore, a condition of no cloud cover and maximum
solar radiation and temperature is ideal condition for carrying out SODIS
experiments. However, this may not be achievable throughout the year and better
conditions are possible during summer days. Chapter 5 discusses the solar radiation
effects
on
disinfection
82
of
water.
5 RESULTS AND DISCUSSION
5.1
Introduction
This chapter discusses the E. coli concentration changes before and after
filtration system and disinfection system separately.
A discussion on individual
performance of four filters, individual performance of four solar troughs in reducing
E. coli concentration at different water flow rates at different solar irradiance values
are done in this chapter.
Water samples are collected at the filters’ inlets, outlets that are troughs’ inlets,
and troughs’ outlets. Twelve samples were collected and tested per sampling event.
Four samples are at inlets of filters that is one at each filter inlet; four samples at filter
outlet or trough inlet that is one sample at each filter outlet and trough inlet; and four
samples at the end of the period or water reaching the desired flow depth.
5.2
Filtration Performance
Four different filters comprising of three different filter materials in different
configurations are tested. Table 5-1 gives the filter specifications and the title given
to them. Filters’ results and performance are discussed individually and the betterperforming
filter
is
83
discussed.
Table 5-1 Filter Specifications and Titles
Filter
Filter Media (cm)
Title
1
Gravel – 27.94; Oyster Shells – 17.78; Sand – 8.89
F1
2
Gravel – 27.94; Oyster Shells – 15.24; Activated Charcoal – 8.89
F2
3
ravel – 27.94; Activated Charcoal – 17.78
F3
4
ravel – 27.94; Oyster Shells – 17.78
F4
5.2.1
Filter 1
Filter 1 is comprised of gravel in the bottom, oyster shells over it and sand on
the top. A maximum of 2.43-log (99.63%) reduction of E. coli concentration is
achieved. Table 5-2 gives the E.coli concentration in water flowing in and flowing
out of F1 along with the percent and log reduction of the E. coli concentration in
2014. Figure 5.1 is the chart developed from the Table 5-2 data.
84
Table 5-2 Filter 1 Performance in E. coli Concentration Reduction in 2014
E. coli Concentration
(CFU/100ml)
E. coli Reduction
Sampled Days
Into Filter
Out of Filter
Percent
Log
30-May
8300
3120
62.41
0.42
04-Jun
910
160
82.42
0.75
06-Jun
820
500
39.02
0.21
10-Jun
1100
870
20.91
0.10
12-Jun
7900
1200
84.81
0.82
16-Jun
660
240
63.64
0.44
17-Jun
290
40
86.21
0.86
01-Jul
490
60
87.76
0.91
03-Jul
8040
30
99.63
2.43
03-Jul
6080
30
99.51
2.31
06-Jul
620
20
96.77
1.49
09-Jul
2930
180
93.86
1.21
16-Jul
1330
290
78.20
0.66
26-Jul
620
40
93.55
1.19
01-Aug
920
110
88.04
0.92
02-Aug
150
10
93.33
1.18
13-Aug
3700
428
88.43
0.94
15-Aug
330
60
81.82
0.74
85
Filter 1 Performance in Reducing E. coli Concentration
9000
10.00
8300
8040
7900
8000
2.43 2.31
6080
7000
1.49
6000
1.21
1.19
5000
4000
0.86
0.82
0.75
0.66
0.21
910
160
820
500
1100
870
0
1330
1200
660
240
0.10
0.94
0.74
1.00
2930
0.44
3000
2000
1.18
0.92
3700
3120
0.42
1000
0.91
290
40
490
60
30
30
620
20
180
290
620
40
920
110
150
10
Out of Filter
Log Reduction
Linear (Into Filter)
Linear (Out of Filter)
Linear (Log Reduction)
Figure 5.1 Filter 1 Performance in Reducing E. coli Concentration
15/Aug
Into Filter
330
60
0.10
13/Aug
2/Aug
1/Aug
26/Jul
16/Jul
9/Jul
6/Jul
3/Jul
3/Jul
1/Jul
17/Jun
16/Jun
12/Jun
10/Jun
6/Jun
4/Jun
30/May
Date (DD-MM)
428
E. coli Log Reduction
86
E.Coli Concentration (CFU/100ml)
10000
Discussion
Filter 1 performance in reducing E. coli concentration improved over time this
may be because of the development of the bio film Schmutzdecke and low pore size.
Usage of fine grain sand sometimes resulted in blockage of the filter. Sedimentation
was not done prior to filters. This allowed suspended particles to enter into filters and
was observed that the sediment is a reason for blocking the pores that are already
small because of the fine sand. At its peak performance (3rd July – 9th July), filter 1 is
effective in reducing E. coli concentration.
This helped in reducing the E. coli
loading on solar disinfection system.
5.2.2
Filter 2
Filter 2 is comprised of gravel in the bottom, oyster shells over it and activated
charcoal on the top.
A maximum of 1.27-log (94.65%) reduction in E. coli
concentration was achieved.
Table 5-3 gives the E.coli concentration in water
flowing in and flowing out of filter 2 along with the percent and log reduction of the
E. coli concentration. Figure 5.2 is the chart developed from the Table 5-3 data.
87
Sampled
Days
(CFU/100ml)
E. coli Reduction
Into Filter
Out of Filter
Percent
Log
30-May
7800
6470
17.05
0.08
4-Jun
600
260
56.67
0.36
6-Jun
720
150
79.17
0.68
6-Jun
760
500
34.21
0.18
10-Jun
1260
370
70.63
0.53
12-Jun
7900
7100
10.13
0.05
16-Jun
520
490
5.77
0.03
17-Jun
360
230
36.11
0.19
25-Jun
4800
2900
39.58
0.22
1-Jul
390
200
48.72
0.29
3-Jul
7600
440
94.21
1.24
3-Jul
5700
2040
64.21
0.45
6-Jul
580
220
62.07
0.42
9-Jul
2110
710
66.35
0.47
16-Jul
1260
1030
18.25
0.09
26-Jul
490
220
55.10
0.35
1-Aug
940
80
91.49
1.07
2-Aug
140
10
92.86
1.15
13-Aug
1780
640
64.04
0.44
15-Aug
350
80
77.14
0.64
19-Aug
1800
184
89.78
0.99
22-Aug
670
68
89.85
0.99
23-Aug
7300
564
92.27
1.11
25-Aug
1670
172
89.70
0.99
26-Aug
1870
100
94.65
1.27
88
89
10.00
9000
8000
7900
7800
7600
7100
7000
6470
1.24
1.15
0.68
5700
0.53
6000
0.36
0.19
0.18
0.45
0.29
4800
5000
7300
1.07
0.47
0.42
1.27
1.11 0.99
0.99 0.99
1.00
0.64
0.44
0.35
0.22
4000
0.09
2900
0.08
3000
0.10
1260
600 720 760
500 370
260 150
1000
2110
2040
0.05
2000
0.03
390
200
520 490360
230
580
220
440
710
0
1260
1030
940
490
220 80 140
10
1670 1870
1800
1780
640 350
80
670
184
564
68
Log Reduction
26/Aug
Out of Filter
25/Aug
23/Aug
22/Aug
19/Aug
15/Aug
13/Aug
2/Aug
1/Aug
26/Jul
16/Jul
9/Jul
6/Jul
3/Jul
3/Jul
1/Jul
25/Jun
17/Jun
16/Jun
12/Jun
10/Jun
6/Jun
6/Jun
4/Jun
30/May
Date (DD-M)
Into Filter
172 100
0.01
E. coli Concentration (CFU/100ml)
10000
Discussion
A maximum of the 1.27-log reduction is achieved in filter 2. But, there are no
events of blockage of the filter. This is due to the usage of activated charcoal, which
is an adsorbing agent. Usage of activated charcoal also helped in reducing the E. coli
concentration because of adsorption.
Using of crushed oyster shells as a filter
material also created more pore size and helped in avoiding blockage.
5.2.3
Filter 3
Filter 3 is comprised of gravel in the bottom, and activated charcoal on the top.
A maximum of 1.08-log (91.67%) reduction in E. coli concentration is achieved.
Table 5-4 gives the E. coli concentration in water flowing in and flowing out of filter
3 along with the percent and log reduction of the E. coli concentration. Figure 5.3 is
the chart developed from the Table 5-4 data.
90
Sampling
Day
(CFU/100ml)
E. coli Reduction
Into Filter
Out of Filter
Percent
Log
30-May
9530
6340
33.47
0.18
4-Jun
540
410
24.07
0.12
6-Jun
550
510
7.27
0.03
10-Jun
1420
310
78.17
0.66
12-Jun
8280
5720
30.92
0.16
16-Jun
540
470
12.96
0.06
17-Jun
360
220
38.89
0.21
1-Jul
350
90
74.29
0.59
3-Jul
7500
1000
86.67
0.88
3-Jul
5200
1170
77.50
0.65
6-Jul
520
290
44.23
0.25
9-Jul
2860
1210
57.69
0.37
16-Jul
1340
1070
20.15
0.10
26-Jul
420
280
33.33
0.18
1-Aug
1010
240
76.24
0.62
2-Aug
120
10
91.67
1.08
13-Aug
1810
800
55.80
0.35
15-Aug
360
120
66.67
0.48
19-Aug
1900
580
69.47
0.52
22-Aug
750
168
77.60
0.65
23-Aug
8600
2054
76.12
0.62
25-Aug
1580
632
60.00
0.40
26-Aug
1900
345
81.84
0.74
91
92
10.00
9000
8600
8280
8000
7000
7500
6340
0.66
6000
1.08
0.88
5720
0.59
5200
0.65
0.62
0.18
4000
0.12
0.18
2860
3000
0.10
0.10
0.06
2000
0.031420
0
800
360
120
580
632
345
0.01
26/Aug
25/Aug
23/Aug
Log Reduction
22/Aug
19/Aug
15/Aug
13/Aug
2/Aug
1/Aug
26/Jul
16/Jul
9/Jul
6/Jul
3/Jul
3/Jul
1/Jul
17/Jun
16/Jun
12/Jun
10/Jun
6/Jun
4/Jun
30/May
Out of Filter
750
168
Date (DD-M)
Into Filter
2054
1900
1580
1900
1810
12101340
1010
1000 1170
1070
540 360 350
520
420
290
280 240120
470
10
220 90
540 550 510
310
410
1000
0.40
0.25
0.21
0.16
0.62
0.48
0.35
0.37
5000
0.74 1.00
0.65
0.52
10000 9530
Discussion
A maximum of the 1.08-log (91.67) reduction is achieved in filter 3.
However, there are no events of blockage of the filter. Usage of activated charcoal
helped in reducing the E. coli concentration because of adsorption.
5.2.4
Filter 4
Filter 4 is comprised of gravel in the bottom, and crushed oyster shells on the
top. A maximum of 0.78-log (83.22%) reduction in E. coli concentration is achieved.
Table 5-5 gives the E. coli concentration in water flowing in and flowing out of filter
4 along with the percent and log reduction of the E. coli concentration. Figure 5.4 is
the chart developed from the Table 5-5 data.
93
Sampling
Day
(CFU/100ml)
E. coli Reduction
Into Filter
Out of Filter
Percent
Log
30-May
9530
5150
45.96
0.27
4-Jun
530
250
52.83
0.33
6-Jun
530
90
83.02
0.77
6-Jun
840
510
39.29
0.22
10-Jun
1320
460
65.15
0.46
12-Jun
6580
5930
9.88
0.05
16-Jun
570
340
40.35
0.22
17-Jun
380
150
60.53
0.40
25-Jun
3570
3150
11.76
0.05
1-Jul
480
190
60.42
0.40
3-Jul
7330
1230
83.22
0.78
3-Jul
5140
1680
67.32
0.49
9-Jul
2290
890
61.14
0.41
16-Jul
1170
810
30.77
0.16
26-Jul
490
270
44.90
0.26
1-Aug
1040
480
53.85
0.34
2-Aug
210
70
66.67
0.48
13-Aug
1810
800
55.80
0.35
15-Aug
360
120
66.67
0.48
19-Aug
1900
580
69.47
0.52
22-Aug
750
168
77.60
0.65
23-Aug
8600
2054
76.12
0.62
25-Aug
1580
632
60.00
0.40
26-Aug
1900
345
81.84
0.74
94
10.00
9530
95
9000
8600
8000
7330
7000
6580
6000
0.27
0.78
0.46
5150
5000
0.74
5930
0.77
0.65
0.40
0.49
0.40
0.33
0.41
5140
4000
0.16
0.10
3000
530 530
250
90
2290
0.05
0.05
1000
0.40
0.26
3570
3150
1320
840
460
510
0.62
0.52
0.48
0.35
0.34
0.22
0.22
2000
0.48
1.00
1230
570
380
340
150
1170
890
810
480
190
1040
490
270
800
360
120
480
210
70
0
2054
1900
1580
1900
1810
1680
580 750
632
168
0.01
Out of Filter
Log Reduction
26/Aug
Into Filter
25/Aug
23/Aug
22/Aug
19/Aug
15/Aug
13/Aug
2/Aug
1/Aug
26/Jul
16/Jul
9/Jul
3/Jul
3/Jul
1/Jul
25/Jun
17/Jun
16/Jun
12/Jun
10/Jun
6/Jun
6/Jun
4/Jun
30/May
Date (DD-M)
345
10000
Discussion
Filter 4 achieved a maximum of 0.78-log (83.22%) reduction in E. coli
concentration. Filter 4’s reduction of E. coli concentration never reached 1-log
(90%). This is due to the high pore size than the other filters, because of the bigger
particle size when compared to sand and activated charcoal.
5.2.5
Filtration discussion
Four filters comprised of three different filter materials in different
proportions are tested in this project. All four filters are successful in reducing the
E.coli concentration. However, filter 1 performed better than rest of three filters by
achieving more than 2-log reduction in two events. Rest of the filters never achieved
a 2-log reduction. Low pore size was created because of using fine sand in filter 1.
This resulted in trapping more E. coli than the other three filters. In addition, the
development of bio-layer on top of sand layer helped increase the reduction of E. coli.
Development of bio-film is not observed in the other three filters. Based on the
maximum percent reduction of E. coli during a single run filter 2 performed better
than filters 3 and 4, and filter 3 performed better than filter 4. A statistical analysis
was carried out on the E.coli reduction data to find out the better performing filter.
The effect of the filters on the E. coli reduction is analysed at a significance level of
90%. A Box Cox transformation of the response variables was performed to make
sure the residual’s assumptions are maintained. With a p-value of 0.003, filter 1 is
shown to be significant in reducing E. coli. A grouping value of A denotes most
significant factor, grouping value B denotes less significant factor. Filter 1 managed a
grouping value of A and the rest of the filters attained grouping value of B. This
shows that filter 1 performed better than rest of the filters. However, filters 2 & 3
96
performed better than filter 4 in attaining greater percent reduction of E. coli in few
runs. Considering all runs has shown that filters 2, 3, and 4 have same significant
levels in reducing E. coli. Table 5-5A shows the grouping values.
Table 5-5A ANOVA Results on Filters’ Performance
5.3
Filter
N
Mean
Grouping
1
18
81.26
A
2
25
64.56
B
3
24
58.42
B
4
23
57.98
B
Solar disinfection is carried out by exposing water flowing in an open channel.
Reason for adopting open channel is for utilizing all the solar radiation reaching the
earth’s surface at the project location. This section discusses the E. coli reduction due
to the solar radiation in all the four troughs. Each trough is painted with different
reflective materials and heat absorbing materials. Table 5-6 gives the paints in four
troughs and the titles give to them for easy reference. Troughs’ performance in four
different testing conditions divided in two phases are discussed and the final
discussion gives the trough that performed better than the other three troughs. Water
flowing into troughs is water flowing out of filters.
Therefore, the E. coli
concentration in water flowing into troughs are the E. coli concentration in water
flowing out of filters.
97
Table 5-6 Trough Specifications and Titles
Trough
Paint
Purpose
Title
1
White
(Brush painted)
Best reflector, and cheap reflecting agent
T1
2
Aluminum
(Spray painted)
Better reflector than White but expensive
T2
3
None
Left unpainted for control
T3
4
Black
(Brush painted)
Absorbs more heat than other materials
T4
5.3.1
Phase I
In phase I the SODIS is tested as static batch system. This involved filling up
the troughs up to 8 inches, which is equal to a volume of 113 gallons. Water is
exposed to sunlight for 2 hours. Table 5-7 gives the E. coli concentration changes in
troughs 1 and 2 during static system testing. Table 5-8 gives the E. coli concentration
changes in troughs 3 and 4 during static system testing. Figures 5.5, 5.6, 5.7 and 5.8
are the charts developed by using the data from tables 5-7 and 5-8. This phase helped
as pre-check for observing the effectiveness of SODIS in reducing the E. coli in water
in an open channel trough, which is different from conventional closed transparent
pipes
SODIS
98
concepts.
Table 5-7 E. coli Concentration Changes in Troughs 1 and 2 during Static Operation
Trough 1
Trough 2
Average Solar
Radiation
Into the Trough
13- May
549.50
670
06 - May
776.50
08 - May
819.00
Date
After 2 hours
Reduction
Into the Trough
Percent
Log
10
98.51
1.83
1070
30
1
96.67
1.48
460
15
96.74
1.49
After 2 hours
Reduction
Percent
Log
115
89.25
0.97
1600
10
99.38
2.20
1100
15
98.64
1.87
99
Table 5-8 E. coli Concentration Changes in Troughs 3 and 4 during Static Operation
Trough 3
Trough 4
Reduction
Average Solar
Radiation
Into the Trough
13- May
549.50
900
06 - May
776.50
08 - May
819.00
Date
After 2 hours
Reduction
Into the Trough
Percent
Log
160
82.22
0.75
930
1630
10
99.39
2.21
1630
5
99.69
2.51
After 2 hours
Percent
Log
192
79.35
0.69
1650
20
98.79
1.92
1370
25
98.18
1.74
E. coli Reduction in Trough 1 When System is Static
10.00
1600
1400
1200
1.83
1.49
1.48
1000
1.00
800
670
600
460
400
200
30
10
1800
15
1
0.10
0
549.50
776.50
819.00
E. coli Concentration into Trough
Log Reduction
Linear (E. coli Concentration out of Trough)
E. coli Concentration out of Trough
Linear (E. coli Concentration into Trough)
Figure 5.5 E. coli Concentration Changes in Trough 1 when System is Static
10.00
1800
1600
1400
1200
1070
2.20
1100
1.87
1000
800
1.00
0.97
600
400
115
200
15
10
0
-200
549.50
776.50
Solar Radiation
819.00
(W/m2)
0.10
Log Reduction
100
1600
2000
10.00
1630
1630
1600
1400
1000
2.51
2.21
1200
900
1.00
800
0.75
600
400
1800
160
200
10
5
0
-200
549.50
776.50
819.00
0.10
Log Reduction
10.00
1650
1600
1370
1400
1200
1000
1.92
930
1.74
800
1.00
0.69
600
400
192
200
25
20
0
-200
549.50
776.50
Solar Radiation
819.00
(W/m2)
0.10
Log Reduction
101
1800
Discussion
All the troughs performed well in this phase. Whereas Trough 3 performed
better in reducing the E. coli concentration in water with log reduction values higher
than 2.0 in couple of events.
This phase helped in finding out that E. coli
concentration can be reduced in water when exposed to sunlight in open channel.
Though it takes more time but financially viable. Results from this phase are not
considered in the analysis for finding out the better performing trough in E. coli
concentration reduction. Because, in phase II water was flowing at different flow
rates.
5.3.2
Phase II
In phase II the SODIS is tested as dynamic system. This involved filling the
troughs up to desired depth in different time intervals. Water depths of 8 inches (113
gallons of water), and 3.5 inches (36.15 gallons of water) are achieved in troughs in
different intervals. Phase has three different scenarios. Results for each scenario is
presented for all the four troughs in following section
5.3.2.1
Scenario I
Flow rate of 32.43 gal/hr is maintained into the troughs for 3.5 hrs to achieve a
water depth of 8.0 inches. The system was started at 9:00 am on the day of testing
and samples were collected at 12:30 pm. But the trough painted white that is attached
to the filter 1 never achieved the desired flow depth because the fine grained sand
used in the filter created low pore size and not allowed water pass through like the
other filters. Tables 5-9, and 5-10 gives the E. coli concentration changes in trough 1
with respect to solar radiation, and pH, temperature respectively. Figures 5.9, 5.10
and 5.11 shows the graphical representation of the relation between E.coli
concentration changes between water at input and output, with respect to average
102
solar radiation, pH and temperature. Solid diamonds shows the E. coli concentration
in water flowing out of the filter and flowing into the troughs. The solid circles show
the reduction in E. coli concentration in troughs. Solid cross points represent the log
reduction of the E. coli concentration. Negative log reduction is not shown in the
charts because negative or zero values cannot be plotted correctly on log charts.
Table 5-9 E. coli Concentration Changes in Trough 1 in Scenario I
Date
Average Solar
Radiation
(W/m2)
E.coli Concentration (Colonies/100ml)
Change
Into Trough
Out of Trough
Difference
Percent
Log
10 - June
381.6
870
650
220
25.29
0.13
30 – May
595.8
3120
1590
1530
49.04
0.29
12 – June
634
1200
166
1034
86.17
0.86
06 – June
666.8
1550
4
1546
99.74
2.59
07 – June
714.2
500
62
438
87.6
0.91
16 - June
727.8
240
36
204
85.0
0.82
Table 5-10 Water pH and Temperature Changes in Trough 1 in Scenario I
pH
Temperature (C)
Average Solar
Radiation
(W/m2)
Into Trough
Out of Trough
Into Trough
Out of Trough
10 - June
381.6
7.85
8.01
23.6
25.9
30 – May
595.8
7.77
7.98
23.9
26.6
12 – June
634
7.72
8.12
22.9
31.4
06 – June
666.8
7.74
8.39
22.3
32.1
07 – June
714.2
7.83
7.98
26.4
23.2
16 - June
727.8
7.72
7.89
21.9
24.8
Date
103
Trough 1 Filled upto 4" over the period of 3.5 hrs
3500
10.00
2500
2000
1.00
1500
1000
E.Coli Concentration (Colonies/100ml)
3000
500
0
0.10
300
400
500
600
700
800
900
Solar Irradiance (W/m2)
E.Coli into Trough
E.Coli out of Trough
Log Reduction
Linear (E.Coli into Trough)
Linear (E.Coli out of Trough)
Figure 5.9 Change in E. coli Concentration in Trough 1 in Scenario I
E. coli Concentration Change and pH
100
3000
80
2500
2000
60
1500
40
1000
20
500
0
Percent Change of E.coli
E.coli Concentration
3500
0
7.5
7.7
7.9
8.1
8.3
8.5
pH
E.coli into Trough
E.coli out of Trough
Percentage Reduction
Linear (E.coli into Trough)
Linear (E.coli out of Trough)
Linear (Percentage Reduction)
Figure 5.10 Relation between Water pH and E. coli Concentration Change in Trough 1
104
E. coli Concentration Change and Temperature
3500
100
80
2500
60
2000
1500
40
1000
20
3000
500
0
0
20
22
24
26
28
30
32
34
Temperature (c)
E.coli into Trough
Percent Change
Linear (Percent Change)
Figure 5.11 Relation between water Temperature and E. coli Concentration Change in
Trough 1
Tables 5-11, and 5-12 gives the E. coli concentration changes in trough
2 with respect to solar radiation, and pH, temperature respectively. Figures
5.12, 5.13 and 5.14 shows the graphical representation of the relation between
E.coli concentration changes between water at input and output, with respect
to average solar radiation, pH and temperature.
105
Table 5-11 E. coli Concentration Changes in Trough 2 when Flow is 32.3gal/hr for 3.5 hrs
Date
Average Solar
Radiation
(W/m2)
Change
Into Trough
Out of Trough
Difference
Percent
Log
10 - June
381.60
370
202
168
45.41
0.26
04 – June
536.40
260
210
50
19.23
0.09
30 – May
595.80
6470
2208
4262
65.87
0.47
12 – June
634.00
7100
2900
4200
59.15
0.39
07 – June
714.20
500
210
290
58.00
0.38
25 – June
721.00
2900
900
2000
68.97
0.51
16 - June
727.80
490
258
232
47.35
0.28
17 - June
871.20
230
176
54
23.48
0.12
pH
Temperature (C)
Average Solar
Radiation
(W/m2)
Out of Filter
In Trough
Out of Filter
In Trough
2014-06-10
381.60
7.84
7.97
22.1
25.1
2014-06-04
536.40
7.88
7.95
24
26.8
2014-05-30
595.80
7.73
7.91
23.7
26.6
2014-06-12
634.00
7.8
7.84
22.7
28.6
2014-06-06
714.20
7.86
7.97
23.7
23.1
2014-06-25
721.00
7.65
7.89
24.9
26.5
2014-06-16
727.80
7.72
7.89
21.8
23.4
2014-06-17
871.20
7.84
8.12
23.7
25.1
Date
106
8000
10.00
6000
1.00
5000
4000
3000
0.10
7000
2000
1000
0
0.01
300
400
500
600
700
800
900
E.Coli into Trough
E.Coli Out of Trough
Log Reduction
Linear (E.Coli Out of Trough)
Figure 5.12 E. coli Concentration Changes in Trough 2 when Flow is 32.3gal/hr for 3.5 hrs
8000
100
80
6000
5000
60
4000
40
3000
2000
20
1000
0
Percent Reduction of E. coli
7000
0
7.5
7.7
7.9
8.1
8.3
8.5
pH
E.coli into Trough
Percent Change
107
E.coli Concentration Change and Temperature
8000
100
7000
5000
60
4000
40
3000
2000
20
1000
0
80
6000
0
20
22
24
26
28
30
32
34
Temperature (C)
E.coli into Trough
Percent Change
Figure 5.14 Relation between Water Temperature and E. coli Concentration Change in
Trough 2
E.coli concentration changes between water at input and output, with respect
to average solar radiation, pH and temperature.
108
Date
Average Solar
Radiation
(W/m2)
Change
Into Trough
Out of Trough
Difference
Percent
Log
10 - June
381.60
310
206
104
33.55
0.18
04 – June
536.40
410
310
100
24.39
0.12
30 – May
595.80
6340
1970
4370
68.93
0.51
12 – June
634.00
5720
2020
3700
64.69
0.45
06 – June
666.80
510
354
156
30.59
0.16
07 – June
714.20
630
384
246
39.05
0.22
25 – June
721.00
4450
1600
2850
64.04
0.44
16 - June
727.80
470
172
298
63.40
0.44
17 - June
871.20
220
152
68
30.91
0.16
Temperature (C)
pH
Date
Average Solar
Radiation
(W/m2)
Out of Filter
In Trough
Out of Filter
In Trough
2014-06-10
381.60
7.82
7.97
21.9
24.6
2014-06-04
536.40
7.86
7.93
23.8
25.6
2014-05-30
595.80
7.71
7.84
24.1
26.3
2014-06-12
634.00
7.68
7.88
22.5
28.4
2014-06-06
666.80
7.81
7.96
22
27.8
2014-06-06
714.20
7.87
8.01
23.4
23
2014-06-25
721.00
7.65
7.89
25.1
29.2
2014-06-16
727.80
7.72
7.89
21.9
26.1
2014-06-17
871.20
7.84
8.12
24.2
28.9
109
Trough 3 Filled upto 8" inches in 3.5 hrs
10.00
6000
5000
4000
1.00
3000
2000
7000
1000
0
300.00
400.00
500.00
600.00
700.00
800.00
0.10
900.00
E.Coli into Trough
Log Reduction
100
6000
80
5000
60
4000
3000
40
2000
20
1000
0
7000
0
7.5
7.7
7.9
8.1
8.3
8.5
pH
E.coli into Trough
Linear (Percent Change of E.coli)
110
7000
100
6000
5000
60
4000
3000
40
2000
80
20
1000
0
0
20
22
24
26
28
30
32
34
Temperature (C)
E.coli into Trough
Percent Change of E.Coli
Linear (Percent Change of E.Coli)
Figure 5.17 Relation between Water Temperature and E. coli Concen tration Change in
Trough 3
E.coli concentration changes in water at input and output, with respect to
average solar radiation, pH and temperature. And figures 5.21 and 5.22
shows the graphical representation of relation between E. coli concentration
change and pH and temperature in all troughs.
111
Date
Average Solar
Radiation
(W/m2)
Change
Into Trough
Out of Trough
Difference
Percent
Log
10 - June
381.60
460
1116
-656
-142.61
-0.38
04 – June
536.40
250
200
50
20.00
0.10
30 – May
595.80
5150
1950
3200
62.14
0.42
12 – June
634.00
5930
1640
4290
72.34
0.56
06 – June
666.80
90
196
-106
-117.78
-0.34
07 – June
714.20
510
260
250
49.02
0.29
25 – June
721.00
3150
1060
2090
66.35
0.47
16 - June
727.80
340
418
-78
-22.94
-0.09
17 - June
871.20
150
272
-122
-81.33
-0.26
pH
Temperature (C)
Average Solar
Radiation
(W/m2)
Out of Filter
In Trough
Out of Filter
In Trough
2014-06-10
381.6
7.87
8.05
22.2
25.9
2014-06-04
536.4
7.82
7.98
24.2
26.9
2014-05-30
595.8
7.75
7.85
24.2
26.8
2014-06-12
634
7.69
7.98
23.2
30.3
2014-06-06
666.8
7.86
8.05
22.7
30.6
2014-06-06
714.2
7.91
8.25
23.3
23.9
2014-06-25
721
7.54
7.87
24.5
26.7
2014-06-16
727.8
7.77
7.99
21.9
25.5
2014-06-17
871.2
7.94
8.12
24.2
27.8
Date
112
Trough 4 Filled upto 8" in 3.5 hrs
5.00
6000
5000
4000
0.50
3000
2000
E.coli Concentration (CFU/100ml)
7000
1000
0
300.00
0.05
400.00
500.00
600.00
700.00
800.00
900.00
E.coli into Trough
Log Reduction
100
6000
80
5000
60
4000
3000
40
2000
20
1000
0
7000
0
7.8
7.85
7.9
7.95
8
8.05
8.1
8.15
8.2
8.25
8.3
pH
E.coli into Trough
Percent reduction
Linear (Percent reduction)
113
7000
100
Percent Reduction E. coli
6000
80
5000
60
4000
3000
40
2000
20
1000
0
0
20
22
24
26
28
30
32
34
Temperature (C)
E.coli into Trough
E.coli Out of Trough
Linear (E.coli Out of Trough)
Trough 4
100
7000
80
6000
5000
60
4000
40
3000
2000
20
1000
0
8000
0
7.5
7.7
7.9
8.1
8.3
8.5
pH
E.coli into Trough
Percent reduction
Figure 5.21 Relation between Water pH and E. coli Concentration Change in all
Troughs in Scenario I
114
E. coli Concentration Change and Temperature
100
7000
80
6000
5000
60
4000
40
3000
2000
20
1000
0
8000
0
20
22
24
26
28
30
32
34
Temperature (C)
E.coli into Trough
Percent reduction
all Troughs in Scenario I
Discussion
In this scenario, none of the troughs’ has achieved at least 1 log-reduction
(90%) of E. coli concentration. This might be because of the less exposure time to
sunlight with high flow rate. Trough 4 has some negative reduction values that shows
an increase in E. coli concentration in the trough at the end of the testing time. This
might be because of the sediments in water reducing the solar radiation penetration to
deeper levels of water in the trough.
Water temperatures in troughs never achieved 38° C, which is the starting
point of the disinfection. SODIS disinfection is independent of water pH between 4.0
and 9.0 (Rincón A-G, Pulgarin, C 2004). Though water pH increased, it was never
115
observed that the final water pH values never reached 9.0 and water never recorded
acidic values.
5.3.2.2
Scenario II
In scenario II a flow rate of 18.8 gal/hr is maintained into the troughs
for 6.0 hrs to achieve a water depth of 8.0 inches. Trough painted white that is
attached to the filter 1 have achieved the desired flow depth in this scenario. Table 517 gives the E. coli concentration changes in troughs when water depth is 0 inches
(time = 0 hrs, 10 am) and 8.0 inches (time = 6.0 hrs, 4 pm). In this scenario, system is
tested during nights that is when solar radiation is 0 W/m2. This showed that E. coli
concentration increases without sunlight and decreases with sunlight. Solid diamonds
shows the E. coli concentration in water flowing out of the filter and flowing into the
troughs. The solid circles show the reduction in E. coli concentration in troughs.
Solid cross points represent the log reduction of the E. coli concentration. Negative
log reduction is not shown in the charts because negative or zero values cannot be
plotted correctly on log charts. Tables 5-17, and 5-18 gives the E. coli concentration
changes in trough 1 with respect to solar radiation, and pH, temperature respectively.
Figures 5.23, 5.24 and 5.25 shows the graphical representation of the relation between
E.coli concentration changes between water at input and output, with respect to
average solar radiation, pH and temperature.
116
Table 5-17 E. coli Concentration Changes in Trough 1 when Flow is 18.8 gal/hr for 6.0 hrs
Date
Average Solar
Radiation
(W/m2)
Change
Into Trough
Out of Trough
Difference
Percent
Log
03 – July
0.00
30
400
-370
-1233.33
-1.12
06 - July
0.00
20
1420
-1400
-7000.00
-1.85
02 – Aug
0.00
10
200
-190
-1900.00
-1.30
26 – July
545.86
40
6
34
85.00
0.82
03 – July
670.71
30
1
29
96.67
1.48
01 – July
830.00
60
38
22
36.67
0.20
01 – Aug
839.57
110
30
80
72.73
0.56
09 – July
850.71
180
30
150
83.33
0.78
16 - July
851.71
290
70
220
75.86
0.62
Table 5-18 Water pH and Temperature Changes in Trough 1 in Scenario I I
pH
Temperature
Average Solar
Radiation
(W/m2)
Out of Filter
In Trough
Out of Filter
In Trough
2014-07-03
0.00
7.95
8.15
20.3
16.3
2014-07-06
0.00
7.79
8.01
20.8
17.4
2014-08-02
0.00
7.8
8.13
21.8
20.9
2014-07-26
545.86
7.55
7.63
29.7
32.6
2014-07-03
670.71
7.35
7.67
23.4
29.5
2014-07-01
830.00
7.55
7.79
26.1
31.2
2014-08-01
839.57
7.73
7.99
24.2
33.3
2014-07-09
850.71
8.11
8.31
28
32.4
2014-07-16
851.71
7.63
7.79
22.2
26.8
Date
117
10.00
1400
1200
1000
800
1.00
600
400
E. coli Log reduction
E. coli Concentration (Colonies/100ml)
1600
200
0
0.10
0
100
200
300
400
500
600
700
800
900
E.Coli into Trough
Log Reduction
Figure 5.23 E. coli Concentration Changes in Trough 1 when Flow is 18.8 gal/hr for 6.0 hrs
100
1400
80
1200
1000
60
800
40
600
400
20
200
0
1600
0
7.5
7.6
7.7
7.8
7.9
8
8.1
8.2
8.3
8.4
pH
E.coli into Trough
Percentage Reduction
Linear (Percentage Reduction)
118
1600
100
80
1200
1000
60
800
40
600
400
1400
20
200
0
0
15
17
19
21
23
25
27
29
31
33
35
Temperature (C)
E.coli into Trough
Trough 1
Tables 5-19, and 5-20 gives the E. coli concentration changes in trough 2 with
respect to solar radiation, and pH, temperature respectively. Figures 5.26, 5.27 and
5.28 shows the graphical representation of the relation between E.coli concentration
changes between water at input and output, with respect to average solar radiation, pH
and temperature.
119
Date
Average Solar
Radiation
(W/m2)
Change
Into Trough
Out of Trough
Difference
Percent
Log
03 – July
0.00
440
860
-420
-95.45
-0.29
06 - July
0.00
220
350
-130
-59.09
-0.20
02 – Aug
0.00
10
30
-20
-200.00
-0.48
26 – July
545.86
220
36
184
83.64
0.79
03 – July
670.71
2040
804
1236
60.59
0.40
01 – July
830.00
200
16
184
92.00
1.10
01 – Aug
839.57
80
28
52
65.00
0.46
09 – July
850.71
710
148
562
79.15
0.68
16 - July
851.71
1030
220
810
78.64
0.67
Table 5-20 Water pH and Temperature Changes in Trough 2 in Scenario II
pH
Temperature (C)
Average Solar
Radiation
(W/m2)
Out of Filter
In Trough
Out of Filter
In Trough
2014-07-03
0.00
7.95
8.15
21.5
17.2
2014-07-06
0.00
7.79
8.01
22.9
18.3
2014-08-02
0.00
7.8
8.13
21.3
20.9
2014-07-26
545.86
7.55
7.63
27.7
32.8
2014-07-03
670.71
7.35
7.67
23.9
31.7
2014-07-01
830.00
7.55
7.79
25.8
32.9
2014-08-01
839.57
7.73
7.99
24.3
33.8
2014-07-09
850.71
8.11
8.31
27.1
32.5
2014-07-16
851.71
7.63
7.79
21.9
26.4
Date
120
10.00
2000
1500
1.00
1000
2500
500
0.10
0
0
100
200
300
400
500
600
700
800
900
E.Coli into Trough
E.Coli Out of Trough
Log Reduction
Linear (E.Coli Out of Trough)
2500
100
2000
80
1500
60
1000
40
500
20
0
0
7.5
7.7
7.9
8.1
8.3
8.5
pH
E.coli into Trough
Percentage Change
Linear (Percentage Change)
121
100
2000
80
1500
60
1000
40
500
20
0
Percent Reduction of E.coli
2500
0
15
20
25
30
35
Temperature
E.coli into Trough
Percent Change
Trough 2
and temperature.
122
Change
Average Solar
Radiation
(W/m2)
Into Trough
Out of Trough
Difference
Percent
Log
03 – July
0.00
1000
1820
-820
-82.00
-0.26
06 - July
0.00
220
290
-70
-31.82
-0.12
02 – Aug
0.00
10
80
-70
-700.00
-0.90
26 – July
545.86
280
92
188
67.14
0.48
03 – July
670.71
1170
684
486
41.54
0.23
01 – July
830.00
90
720
-630
-700.00
-0.90
01 – Aug
839.57
240
180
60
25.00
0.12
09 – July
850.71
1210
1632
-422
-34.88
-0.13
16 - July
851.71
1070
292
778
72.71
0.56
Date
pH
Temperature (C)
Average Solar
Radiation
(W/m2)
Out of Filter
In Trough
Out of Filter
In
Trough
2014-07-03
0.00
7.95
8.15
21.7
18.7
2014-07-06
0.00
7.79
8.01
22.7
18.4
2014-08-02
0.00
7.8
8.13
21.2
21.1
2014-07-26
545.86
7.55
7.63
26.4
32.1
2014-07-03
670.71
7.35
7.67
24.1
30.2
2014-07-01
830.00
7.55
7.79
25.7
31.9
2014-08-01
839.57
7.73
7.99
24.8
32.8
2014-07-09
850.71
8.11
8.31
26.5
32.5
2014-07-16
851.71
7.63
7.79
21.8
26.1
Date
123
10.00
1800
1600
1400
1200
1000
1.00
800
600
2000
400
200
0
0
200
400
600
0.10
1000
800
E.Coli into Trough
Log Reduction
100
1800
1600
80
1400
1200
60
1000
800
40
600
400
20
200
0
2000
0
7.5
7.6
7.7
7.8
7.9
8
8.1
8.2
8.3
8.4
pH
E.coli into Trough
Percent reduction
124
Temperature and E.coli Concentration
2000
100
1600
80
1400
1200
60
1000
800
40
600
400
20
1800
200
0
0
15
20
25
30
35
Temperature (C)
E.coli into Trough
Percent Change
Trough 3
and temperature. Figures 5.35 and 5.36 shows the graphical representation of relation
between E. coli concentration change and final pH and final temperature in all troughs
during scenario II.
125
Date
Average Solar
Radiation
(W/m2)
Change
Into Trough
Out of Trough
Difference
Percent
Log
03 – July
0.00
1230
3550
-2320
-188.62
-0.46
06 - July
0.00
70
80
-10
-14.29
-0.06
26 – July
545.86
270
52
218
80.74
0.72
03 – July
670.71
1680
884
796
47.38
0.28
01 – July
830.00
190
1200
-1010
-531.58
-0.80
01 – Aug
839.57
480
244
236
49.17
0.29
09 – July
850.71
890
684
206
23.15
0.11
16 - July
851.71
810
328
482
59.51
0.39
pH
Temperature (C)
Average Solar
Radiation
(W/m2)
Out of Filter
In Trough
Out of Filter
In Trough
2014-07-03
0.00
7.93
8.1
23.2
18.9
2014-08-02
0.00
7.97
8.14
21.7
21
2014-07-26
545.86
7.68
7.82
27.5
33.5
2014-07-03
670.71
7.35
7.5
23.9
32.3
2014-07-01
830.00
7.99
8.23
25.8
33.5
2014-08-01
839.57
7.89
8.03
24.4
32.8
2014-07-09
850.71
8.35
8.49
26.2
34.1
2014-07-16
851.71
7.75
7.87
21.9
26.8
Date
126
4000
10.00
3000
2500
2000
1.00
1500
3500
1000
500
0
0
200
400
600
800
0.10
1000
E.Coli into Trough
Log Reduction
4000
100
80
3000
2500
60
2000
40
1500
1000
20
Percent Change of E. coli
3500
500
0
0
7.5
7.7
7.9
8.1
8.3
8.5
pH
E.coli into Trough
Percent reduction
127
4000
100
3500
80
3000
2500
60
2000
40
1500
1000
20
500
0
0
15
20
25
30
35
Temperature (C)
E.coli into Trough
Percent Change
Trough 4
100
3500
80
3000
2500
60
2000
40
1500
1000
20
500
0
4000
0
7.5
7.7
7.9
8.1
8.3
8.5
pH
E.coli into Trough
Percentage Change
Troughs in Scenario II
128
100
3500
80
3000
2500
60
2000
40
1500
1000
20
500
0
4000
0
15
20
25
30
35
Temperature (C)
E.coli into Trough
Percentage Change
all Troughs in Scenario II
Discussion
In this scenario, Trough 1 performed better than other with a maximum of
1.48 log reduction and no increase in E. coli reduction.
In this scenario, SODIS is
tested in the night-time where solar radiation of is 0 W/m2. E. coli concentration has
increased when tested the system in morning. Troughs 3 and 4 have some negative
reduction values shows an increase in E. coli concentration in the trough at the end of
the testing time during the sunny time. One reason behind this might be the sediments
in water reducing the solar radiation penetration to deeper levels of water in the
trough.
In addition, the other reason can be the result of ideal conditions for
incubation of E. coli, which is temperature of 35° C, availability of nutrients, as the
water used for testing the system is from an urban stream, and availability of nutrients
in urban streams is proven high. Water temperatures in troughs never achieved the
129
disinfection beginning temperature, which is 38° C. Water pH never recorded values
below 4.0 or above 9.0.
5.3.2.3
Scenario III
Flow rate of 7.3 gal/hr is maintained into the troughs for 5.0 hrs to achieve a
water depth of 3.5 inches. Trough painted white is connected to the filter 1 have
achieved the desired flow depth in this scenario.
Table 5-25 gives the E. coli
concentration changes in troughs when water depth is 0 inches (time = 0 hrs) and 3.5
inches (time = 5.0 hrs. Tables 5-25, and 5-26 gives the E. coli concentration changes
in trough 1 with respect to solar radiation, and pH, temperature respectively. Figures
5.37, 5.38 and 5.39 shows the graphical representation of the relation between E.coli
concentration changes between water at input and output, with respect to average
solar radiation, pH and temperature.
Date
Average Solar
Radiation
(W/m2)
Change
Into Trough
Out of Trough
Difference
Percent
Log
23 – Aug
556.17
6120
1550
4570
74.67
0.60
22 – Aug
582.17
460
32
428
93.04
1.16
25 – Aug
632.17
11200
142
11058
98.73
1.90
26 – Aug
699.83
1760
308
1452
82.50
0.76
15 – Aug
796.67
60
1
59
98.33
1.78
19 – Aug
799.50
112
1
111
99.11
2.05
13 - Aug
821.83
428
1
427
99.77
2.63
130
Table 5-26 Water pH and Temperature Changes in Trough 1 in Scenario III
pH
Temperature (C)
Average Solar
Radiation
(W/m2)
Out of Filter
In Trough
Out of Filter
In Trough
2014-08-13
821.83
7.64
7.81
23.8
31
2014-08-15
556.17
7.85
7.99
28.5
32.9
2014-08-19
796.67
7.78
7.88
23.2
27.9
2014-08-22
799.5
8.21
8.32
29.6
36.6
2014-08-23
632.17
8.25
8.32
30.3
35.7
2014-08-25
699.83
8.16
8.28
25.8
36.2
2014-08-26
582.17
7.98
8.15
28.8
35.6
Date
Trough 1 Filled upto 3.5" over the period of 5.0 hrs
10.00
10000
8000
6000
1.00
4000
12000
2000
0
0.10
500
550
600
650
700
750
800
850
E.Coli into Trough
Log Reduction
131
100
10000
80
8000
60
6000
40
4000
20
2000
0
12000
0
7.5
7.6
7.7
7.8
7.9
8
8.1
8.2
8.3
8.4
8.5
pH
E.coli into Trough
Percent reduction
Temperature and E.coli Concentration Change
100
10000
80
8000
60
6000
40
4000
12000
20
2000
0
0
25
27
29
31
33
35
37
39
Temperature (C)
E.coli into Trough
Percent Change
Trough 1
132
and temperature.
Date
Average Solar
Radiation
(W/m2)
Change
Into Trough
Out of Trough
Difference
Percent
Log
23 – Aug
556.17
564
120
444
78.72
0.67
22 – Aug
582.17
68
1
67
98.53
1.83
25 – Aug
632.17
172
44
128
74.42
0.59
26 – Aug
699.83
100
10
90
90.00
1.00
15 – Aug
796.67
80
8
72
90.00
1.00
19 – Aug
799.50
184
4
180
97.83
1.66
13 - Aug
821.83
640
70
570
89.06
0.96
133
pH
Temperature (C)
Average Solar
Radiation
(W/m2)
Out of Filter
In Trough
Out of Filter
In Trough
2014-08-13
821.83
7.57
7.65
23.1
31.2
2014-08-15
556.17
8.15
8.30
28.2
33.8
2014-08-19
796.67
7.74
7.82
22.8
29.8
2014-08-22
799.50
8.00
8.24
27.2
36.4
2014-08-23
632.17
8.07
8.35
29.1
35.6
2014-08-25
699.83
8.24
8.36
27.2
37.5
2014-08-26
582.17
8.07
8.19
28.6
36.3
Date
700
10.00
600
500
400
1.00
300
200
Trough 2 Filled upto 3.5" over the period of 5.0 hrs
100
0
0.10
500
550
600
650
700
750
800
850
E.Coli into Trough
Log Reduction
134
100
600
80
500
60
400
300
40
200
20
100
0
700
0
7.50
7.70
7.90
E.coli into Trough
8.10
pH
8.30
8.50
Percent Reduction
Linear (Percent Reduction)
700
100
80
500
60
400
300
40
200
20
600
100
0
0
25
27
29
31
33
35
37
39
Temperature (C)
E.coli into Trough
Percent Change
Trough 2
135
and temperature.
Change
Average Solar
Radiation
(W/m2)
Into Trough
Out of Trough
Difference
Percent
Log
23 – Aug
556.17
2054
740
1314
63.97
0.44
22 – Aug
582.17
168
1
167
99.40
2.23
25 – Aug
632.17
632
104
528
83.54
0.78
26 – Aug
699.83
345
10
335
97.10
1.54
15 – Aug
796.67
120
14
106
88.33
0.93
19 – Aug
799.50
580
50
530
91.38
1.06
13 - Aug
821.83
800
70
730
91.25
1.06
Date
136
Average Solar
Radiation
(W/m2)
Date
pH
Temperature (C)
Out of Filter
In Trough
Out of Filter
In Trough
2014-08-13
796.67
7.80
7.94
23.1
29.7
2014-08-15
799.50
7.93
8.09
26.7
35.9
2014-08-19
582.17
8.02
8.17
28.7
36.5
2014-08-22
556.17
8.19
8.32
28.8
33.3
2014-08-23
821.83
7.57
7.65
23.3
31.3
2014-08-25
699.83
8.15
8.46
27.3
37.4
2014-08-26
632.17
8.04
8.20
28.4
35
Trough 3 Filled upto 3.5" in 5.0 hrs
10.00
2000
1500
1.00
1000
2500
500
0.10
0
500
550
600
650
700
750
800
850
E.Coli into Trough
Log Reduction
Figure 5.43 E. coli Concentration Changes in Trough 3 when Flow is 7.3 gal/hr for 5.0 hr s
137
2500
100
2000
80
1500
60
1000
40
500
20
0
0
7.60
7.70
7.80
7.90
8.00
8.10
8.20
8.30
8.40
8.50
8.60
pH
E.coli into Trough
Percent Reduction
2500
100
2000
80
1500
60
1000
40
500
20
0
0
25
27
29
31
33
35
37
39
Temperature (C)
E.coli into Trough
Percent Reduction
Trough 3
138
and temperature. Figures 5.49 and 5.50 shows the graphical representation of relation
between E. coli concentration change and final pH and final temperature in all troughs
during scenario II.
Change
Average Solar
Radiation
(W/m2)
Into Trough
Out of Trough
Difference
Percent
Log
23 – Aug
821.83
925
50
875
94.59
1.27
22 – Aug
799.50
240
4
236
98.33
1.78
25 – Aug
796.67
76
16
60
78.95
0.68
26 – Aug
699.83
452
10
442
97.79
1.66
15 – Aug
632.17
864
440
424
49.07
0.29
19 – Aug
582.17
200
8
192
96.00
1.40
13 - Aug
556.17
420
34
386
91.90
1.09
Date
139
pH
Temperature
Average Solar
Radiation
(W/m2)
Out of Filter
In Trough
Out of Filter
In Trough
2014-08-13
821.83
7.66
7.87
23.3
33
2014-08-15
632.17
8.05
8.13
27.7
34.1
2014-08-19
796.67
7.84
7.98
24.1
31.4
2014-08-22
699.83
8.15
8.26
27.3
38
2014-08-23
556.17
8.16
8.30
28.8
35
2014-08-25
582.17
8.04
8.26
28.7
36.9
2014-08-26
799.50
8.02
8.24
27.5
37.1
Date
Trough 4 Filled upto 3.5" in 5.0 hrs
10.00
900
800
700
600
1.78
1.66
1.40
1.27
1.09
500
1.00
0.68
400
300
0.29
200
1000
100
0.10
0
500
550
600
650
700
750
800
850
E.coli into Trough
Log Reduction
140
100
900
800
80
700
600
60
500
400
40
300
200
1000
20
100
0
0
7.80
7.90
8.00
8.10
8.20
8.30
8.40
pH
E.coli into Trough
Percent reduction
1000
100
800
80
700
600
60
500
400
40
300
200
20
900
100
0
0
25
27
29
31
33
35
37
39
Temperature (C)
E.coli into Trough
Percent Reduction
Trough 4
141
100
10000
80
8000
60
6000
40
4000
20
2000
0
12000
0
7.6
7.8
8
8.2
8.4
8.6
pH
E.coli into Trough
Percent reduction
Troughs in Scenario III
100
10000
80
8000
60
6000
40
4000
20
2000
0
12000
0
25
27
29
31
33
35
37
39
Temperature (C)
E.coli into Trough
Percent Reduction
all Troughs in Scenario III
142
Discussion
In this scenario all troughs performed better than the previous scenarios. None
of the troughs recorded negative values in E. coli reduction. This is due to the
reduced targeted flow depth. Trough 1 performed better than the other troughs. E.
coli concentration of 0 colony/100ml is expressed as 1 colony/100ml in the data tables
above. This is done because when the end concentration is zero the percentage
reduction will be 100%. And expressing a 100% reduction in log reduction is not
possible.
Water temperatures in troughs reached 38° C during one event in trough 4.
Water pH never recorded values below 4.0 or above 9.0.
5.3.3
SODIS Discussion
E. coli reduction is observed in all four troughs in all the scenarios. By
observation, all four troughs performed better in scenario III in reducing E. coli
concentration. A statistical analysis was performed on all the three scenarios for
finding out the better performed scenario and trough in reducing the E. coli
concentration. For this irradiation values are divided into three groups. Group 1
denotes the values between 0 W/m2 and 600 W/m2; group 2 denotes values between
601 W/m2 and 750 W/m2; group 3 denotes values between 751 W/m2 and 900 W/m2.
The effects of the different factors on the E. coli reduction is analysed at a
significance level of 95%. A Box Cox transformation of the response variables was
performed to make sure the residual’s assumptions are maintained. With a p-value of
0.075, scenario and irradiation; trough and irradiation combinations are shown to be
significant. Table 5-33 shows the ANOVA results obtained from Minitab. The
significant features are Scenario, Trough, and the interaction between Scenario and
143
Irradiation Group, Trough and Irradiation Group. The associated p-values of their
significance is highlighted in the table 5-33.
Table 5-33 ANOVA Results from Minitab
Source
Scenario
Trough
Irr Grp
Scenario*Trough
Scenario*Irr Grp
Trough*Irr Grp
Error
Total
DF
2
3
2
6
4
6
53
76
Seq SS
315495681
57768336
8110314
38100295
61232405
44231871
190702891
715641793
Adj SS
249546733
49811552
6063429
21397299
65511641
44231871
190702891
Adj MS
124773367
16603851
3031715
3566216
16377910
7371978
3598168
F
34.68
4.61
0.84
0.99
4.55
2.05
P
0.000
0.006
0.436
0.441
0.003
0.075
The ANOVA shows that the factors mentioned above are significant. To better
understand the levels at which the performance is significant, a pairwise Tukey test is
performed on these factors. The results of the pairwise Tukey test are shown in Table
5-34 and 5-35. Grouping denotes the grading of the parameters. The grouping value A
denotes most significant factor, grouping value, B denotes significance better than C
and D. The Scenario III at Irradiation groups 1, 2 and 3 are the ones, which have
statistically significant highest percentage reduction in the E. coli concentration. This
is because of the reduced flow rate that resulted in attaining compared to other
scenarios, which resulted in increased solar radiation penetrated in to deeper depth of
water. Troughs 1 and 2 with maximum grouping value A are significant in reducing
E. Coli when compared to troughs 3 and 4 who have maximum grouping value B.
Scenario III which have reduced depth because of reduced flow rate when compared
to previous scenarios. The time of exposure for scenario III is 5.0 hrs which is greater
than scenario I and lower than scenario II. In the same way, flow depth attained in
scenario III is lower than scenarios II and I. All three irradiation groups in scenario III
attained a grouping value of A, which have not happened with the other two scenarios
with respect to three irradiation groups. This proves that flow depth is also an
144
important factor along with irradiation in reducing E. coli in water. Therefore, it can
be stated that a low flow depth with a high irradiation value can help in better
reduction of E. coli.
Table 5-34 Tukey Test Results for Scenario, Irradiance and E. coli Reduction
Scenario
III
III
III
II
I
II
II
I
I
Irr Grp
3
1
2
1
2
2
3
1
3
N
12
8
8
4
16
4
13
10
2
Mean
8698.1
7721.9
7321.4
6311.8
4569.8
4246.4
4015.3
2115.2
968.5
Grouping
A
AB
ABC
CD
BCD
CD
D
D
CD
Table 5-35 Tukey-Test Results for Trough Performance
5.4
Trough
N
Mean
Grouping
1
19
6362.7
A
2
21
5351.6
AB
3
20
4230.6
B
4
17
4485.4
B
Conclusion
Summary of Findings
Filter 1 and Trough 1 performed better in reducing E. coli concentration.
Filter 1 performance increased gradually and the percentage drops is because of the
frequent disturbance applied on the top layers of the sand for increased out flow rate
from the filter. Trough 1 had reduced bacterial loading because of the sand filter
(Filter 1) connected to the trough. This also helped in better performance of the
trough in SODIS in reducing the E. coli concentration. pH and temperatures have
never achieved the disinfection standards. Reduction of water depth from 8 inches to
145
3.5 inches, though the average receiving solar radiation decreased, increased the
efficiency of all the four troughs. This is also demonstrated by the statistical analysis
of the SODIS. NPDES’ 2012 recreational water quality report states that an average
30-day E. coli concentration in water should not exceed 126 colonies/100ml to access
water for recreation. Table 5-36 shows the average of the E. coli concentration at the
outlet of troughs in scenario III. Troughs 2 and 4 performed better in achieving the
targeted E. coli concentration for recreational water. However, when compared the
amount of E. coli reduction trough 1 performed better than rest of the three. Table 537 shows the number testing events per filter and number of occasions a filter
achieved the NPDES’ limit on E. coli concentration in recreational water. Filter 1
performed better than rest of the three filters in achieving the limits in 9 occasions out
of 18 testing events.
Research Contribution
The previous discussion illustrates that open channel SODIS can be an
effective off-stream water treatment concept for reducing the E. coli concentration.
SODIS can perform better if a filtration unit is installed prior to it.
Optical
inactivation of bacteria in water by sunlight is achievable with reduced suspended
particles and lower flow depths. This is demonstrated in the scenario III, in which
water depth was reduced from previous scenarios. The reduction in outflow rate from
filters increased the retention time in filters, increased the filters performance, and
reduced the suspended particles loading on SODIS system. In this study, system 1 that
consists of Filter 1 and Trough 1 performed better than other systems.
146
Table 5-36 SODIS’ Performance in Achieving NPDES RWQ Report 2012
Trough
1
2
3
4
Average E. coli Concentration
(colonies/100ml)
290.71
36.71
141.3
80.3
No. of Occasions When Minimum E.
coli concentration is achieved in 7
events
4
7
6
6
Table 5-37 Filters’ Performance in Achieving NPDES RWQ Report 2012
Filter
1
2
3
4
Number of Testing Events
18
25
24
23
No. of Occasions When Minimum E.
coli concentration is achieved
9
5
3
3
Environmental Education and Community Engagement
This project is one of the components of Beargrass Falls which is serving as a
public display of renewable and sustainable urban runoff pollutant reduction concepts.
Project is constructed on the bank of Beargrass creek near the MSD pumping station.
Raw water used for this project is drawn from the Beargrass creek, an urban stream in
Louisville metro area. The urban stream is highly polluted and access is restricted to
public for recreational activities. Beargrass fall is developed as an educational and
informational place to increase the awareness about urban stream protection in public.
These concepts involve adoption of best management practices (BMPs) like pervious
pavements (by MSD), rain garden and rain barrels (by University of Kentucky). These
BMPs help in reducing the polluted rain water runoff getting into the urban streams
and this helps in reducing the pollution levels in streams. In other way this project
also helps in reducing the pollution but post pollution getting into the streams.
147
To achieve these educational sessions for students are being conducted by UofL
Civil Engineering Dept. and Get Outdoors Kentucky. The sessions start with students
going on canoe tour on Beargrass creek. Students were taught about history of
Beargrass creek, urbanization effects on streams, and stress on ecology in streams due
to pollution. The final step of this tour is visiting the park and learning about the
sustainable concepts in reducing the pollution flowing into the creek. This project is
located in the Butcher Town green way. The hikers, bikers and runners accessing the
greenway stops at the park and learn about the sustainable concepts. International
exchange student groups visited the park for learning the sustainable concepts.
5.5
Recommendations and Future Work
It is demonstrated that E. coli concentration reduction due to solar radiation
can be increased by reducing water depth. This project used the semi-circular troughs
for SODIS.
An increased water surface area and decreased water depth can
effectively increase the E. coli reduction. Usage of an half elliptical shaped trough
can increase water surface area exposed to sun light than the semi-circular trough and
reduced water depth helps in increasing the solar radiation effects at deeper depths. E.
coli is used as the indicator of biological water quality. Analysing water samples for
bacteria other than E. coli can help in testing the system’s efficiency in changing the
other bacterial concentrations. Filters’ performance can be increased by increasing
the retention time of water in filter. This can be achieved by reducing the inflow and
outflow. Reduction of inflow also helps in reducing the overflow of water from the
filters. And also introduction of sedimentation chamber prior to filtration can reduce
the loading on filters. A combination of filtration and SODIS can achieve better
reduction of E. coli. This project considered E. coli as water quality indicator. It will
be better to analyze water samples for other bacterial and virus concentrations. As the
148
raw water used for this project is drawn from Beargrass creek, which is a polluted
urban stream and water is polluted with all the possibilities from biological (sewer
over flows, dry leaves. etc) to chemical (gasoline from street surface, fertilizers from
gardens and back yards. etc), usage of better quality raw water for treatment can
result in achieving the better purification and better output water quality.
149
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156
APPENDIX A
STATISTICAL ANALYSIS RESULTS
A.1
General Linear Model: Percent Reduction of E. coli by Filters
Method
Factor coding
(-1, 0, +1)
Box-Cox transformation
Rounded λ
1.4218
Estimated λ
1.4218
90% CI for λ
(1.07830, 1.79530)
Factor Information
Factor Type Levels Values
Filter Fixed
4 1, 2, 3, 4
Analysis of Variance for Transformed Response
Source
Filter
Error
Total
DF Adj SS Adj MS F-Value P-Value
3 501597 167199 5.04 0.003
86 2854762 33195
89 3356359
Model Summary for Transformed Response
S R-sq R-sq(adj) R-sq(pred)
182.195 14.94% 11.98%
6.94%
Coefficients for Transformed Response
Term
Coef SE Coef T-Value P-Value VIF
Constant 385.0 19.4 19.88 0.000
Filter
1
134.4 36.0 3.73 0.000 1.63
2
-10.6 32.2 -0.33 0.744 1.53
3
-63.6 33.1 -1.92 0.058 1.5z
Regression Equation
157
Percent Reduction^1.4218 = 385.0 + 134.4 Filter_1 - 10.6 Filter_2 - 63.6 Filter_3
- 60.2 Filter_4
Residual Plots for Percent Reduction
Comparisons for Percent Reduction
Tukey Pairwise Comparisons: Response = Percent Reduction, Term = Filter
Grouping Information Using the Tukey Method and 90% Confidence
Filter N Mean Grouping
1
18 81.2633 A
2
25 64.5554
B
4
24 58.4153
B
3
23 57.9762
B
Means that do not share a letter are significantly different.
A.2
General Linear Model: Log Reduction
Method
Factor coding
(-1, 0, +1)
Rounded λ
0.5
Estimated λ
0.415773
158
90% CI for λ
(0.253273, 0.581273)
Factor Information
Filter Fixed
4 1, 2, 3, 4
Source
Filter
Error
Total
3 1.376 0.45883 6.90 0.000
86 5.717 0.06648
89 7.094
0.257840 19.40% 16.59%
11.53%
Term
Constant 0.7172 0.0274 26.17 0.000
Filter
1
0.2233 0.0510 4.38 0.000 1.63
2
-0.0198 0.0456 -0.43 0.665 1.53
3
-0.1023 0.0469 -2.18 0.032 1.55
Regression Equation
Log Reduction^0.5 = 0.7172 + 0.2233 Filter_1 - 0.0198 Filter_2 - 0.1023 Filter_3
- 0.1012 Filter_4
159
Residual Plots for Log Reduction of E. coli by Filters
Comparisons for Log Reduction
Tukey Pairwise Comparisons: Response = Log Reduction, Term = Filter
Filter N Mean Grouping
1
18 0.884643 A
2
25 0.486361
B
4
24 0.379458
B
3
23 0.378171
B
160
A.3
General Linear Model: Percent reduction of E. coli by SODIS
Method
Factor coding
(-1, 0, +1)
Rounded λ
2
Estimated λ
1.82657
90% CI for λ
(1.34307, 2.34107)
Factor Information
Scenario Fixed
3 1, 2, 3
Thorousgh Fixed
4 1, 2, 3, 4
Solar Radiation Fixed
3 1, 2, 3
Source
Scenario 2 304133625 152066812 31.39 0.000
Thorousgh 3 57025931 19008644 3.92 0.012
Solar Radiation
2 8110314 4055157 0.84 0.437
Error
69 334267462 4844456
Lack-of-Fit 26 171494333 6595936 1.74 0.052
Pure Error 43 162773129 3785422
Total
76 715641793
2201.01 53.29% 48.55%
41.45%
Term
Constant 5341 256 20.87 0.000
Scenario
1
-2004 398 -5.04 0.000 1.83
2
-693 405 -1.71 0.092 1.64
Thorousgh
1
1398 438 3.19 0.002 1.42
2
48 424 0.11 0.909 1.40
3
-829 433 -1.92 0.060 1.42
Solar Radiation
1
-360 376 -0.96 0.342 1.42
2
444 370 1.20 0.235 1.56
Regression Equation
Percent reduction^2 = 5341 - 2004 Scenario_1 - 693 Scenario_2 + 2697 Scenario_3
+ 1398 Thorousgh_1 + 48 Thorousgh_2 - 829 Thorousgh_3 - 618 Thorousgh_4 - 360 Solar
Radiation_1 + 444 Solar Radiation_2 - 84 Solar Radiation_3
Residual Plots for Percent reduction
161
Comparisons for Percent reduction
Tukey Pairwise Comparisons: Response = Percent reduction, Term = Scenario
Scenario N Mean Grouping
3
28 89.6542 A
2
21 68.1717
B
1
28 57.7635
B
Tukey Pairwise Comparisons: Response = Percent reduction, Term = Thorousgh
Thorousgh N Mean Grouping
1
19 82.0895 A
2
21 73.4099 A B
4
17 68.7225
B
3
20 67.1717
B
Tukey Pairwise Comparisons: Response = Percent reduction, Term = Solar Radiation
Solar Radiation N Mean Grouping
2
28 76.0558 A
3
27 72.5003 A
1
22 70.5770 A
A.4
General Linear Model: Log reduction of E. coli by SODIS
162
Method
Factor coding
(-1, 0, +1)
Rounded λ
0.195768
Estimated λ
0.195768
90% CI for λ
(0.00926810, 0.383268)
Factor Information
Scenario Fixed
3 1, 2, 3
Thorousgh Fixed
4 1, 2, 3, 4
Solar Radiation Fixed
3 1, 2, 3
Source
Scenario 2 0.65219 0.32609 28.44 0.000
Thorousgh 3 0.13624 0.04541 3.96 0.012
Solar Radiation
2 0.02798 0.01399 1.22 0.302
Error
69 0.79129 0.01147
Lack-of-Fit 26 0.35727 0.01374 1.36 0.181
Pure Error 43 0.43403 0.01009
Total
76 1.62384
0.107089 51.27% 46.33%
39.02%
Term
Constant 0.8997 0.0125 72.26 0.000
Scenario
1
-0.0905 0.0194 -4.67 0.000 1.83
2
-0.0351 0.0197 -1.78 0.080 1.64
Thorousgh
1
0.0700 0.0213 3.29 0.002 1.42
2
-0.0027 0.0206 -0.13 0.898 1.40
3
-0.0386 0.0210 -1.83 0.071 1.42
Solar Radiation
1
-0.0208 0.0183 -1.14 0.258 1.42
2
0.0262 0.0180 1.46 0.150 1.56
Regression Equation
Log red^0.195768 = 0.8997 - 0.0905 Scenario_1 - 0.0351 Scenario_2 + 0.1255 Scenario_3
+ 0.0700 Thorousgh_1- 0.0027 Thorousgh_2- 0.0386 Thorousgh_3- 0.0288 Thorousgh_4 0.0208 Solar Radiation_1 + 0.0262 Solar Radiation_2 - 0.0054 Solar Radiation_3
Residual Plots for Log red
163
Comparisons for Log red
Tukey Pairwise Comparisons: Response = Log red, Term = Scenario
Scenario N Mean Grouping
3
28 1.13562 A
2
21 0.47562
B
1
28 0.33908
B
Tukey Pairwise Comparisons: Response = Log red, Term = Thorousgh
Thorousgh N Mean Grouping
1
19 0.854503 A
2
21 0.573941 A B
4
17 0.493536
B
3
20 0.465841
B
Tukey Pairwise Comparisons: Response = Log red, Term = Solar Radiation
Solar Radiation N Mean Grouping
2
28 0.674836 A
3
27 0.565027 A
1
22 0.517024 A
164
APPENDIX B
PRESENTATION
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Appendix C
Draft of Article Published in Sustain Magazine
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CURRICU U
VITA
Venkata D. Gullapalli
Motivation
To work in a creative environment that uses my skill and experience to the fullest and
gives adequate exposure and scope to emerging and evolving technologies.
Education
Louisville, Ky
 Ph.D. in Civil Engineering
April 2015
Advisor: Dr. Mark N. French
Research Project: Green Water Treatment Project
 Master of Science in Civil Engineering
August 2008
Advisor: Dr. Mark N. French
Research Project & Masters Thesis: Reuse of treated filter wash water as source
of flow augmentation
Acharya Nagarjuna University
April 2006
Guntur, India
 Bachelor of Technology in Civil Engineering
Research Experience
Louisville, Ky
Water Treatment Using Sustainable Engineering Concepts
May 2012 – TD
Partners: Kentucky Institute for Environmental Sustainable Design (KIESD), MSD
Louisville, District 9 Louisville, Get out Doors Kentucky
A pilot water treatment project was designed and being tested, which uses naturally
available materials for water filtration, and solar radiation for disinfection. This pilot
project is a part of Beargrass Falls, a sustainable and educational project.
Duties:
 Reviewed past and present techniques and research projects in water treatment
 Pilot project design, construction, maintenance and operations
 Testing different reflective surfaces to find out the effective and viable
reflective material
 Designed and developed standard operating procedures (SOPs) for conducting
laboratory analysis
 Certified for performing Biosafety level2 (BSL 2) analysis
 Collected and tested water samples for bacterial concentration, pH, DO,
Temperature, TDS, TSS, Conductivity and Nutrients
Reuse of Treated Filter Wash Water as Source of Flow Augmentation
Feb 2007 - Aug 2008
Partners: Center for Infrastructure Research, Louisville Water Company,
Metropolitan Sewer District (MSD) Louisville, KY
This project tested the feasibility of treated filter backwash water as source for stream
flow
augmentation
207
Duties:
 Reviewed NPDES, KPDES and Clean Water Act to check the pollution
release regulations and drinking water standards
 Collected and tested water samples from Beargrass Creek (Louisville, KY),
and filter wash water from Louisville Water Company
 Reviewed water quality reports from historical records
 Reviewed water flow quantities in Beargrass creek from historical records
 Conducted field work for pipe line locations and stream discharge points for
storm sewer outlets
 Prepared technical report summarizing project feasibility
Acharya Nagarjuna University
Guntur, India
Estimation of accident rate on NH9
Vijayawada, India
Central Road Research Institute, New Delhi, India
This project involves counting the vehicles manually, measuring speeds of vehicles by
using speed guns and reporting the data to Central Road Research Institute for design
references.
Seismic Design of Buildings
Vijayawada, India
Undergraduate final project
This project tested and analyzed the feasibility of incorporation of international
seismic design standards into Indian design standards.
Professional Experience and Activities
Instructor
Beargrass Falls Park,
Louisville Ky
 Conducted informative sessions on water and its importance
 Sessions conducted for community partners and students
 Teaching materials prepared for diverse audience ranging from general public
to middle school students
 Sessions conducted to students attending Health and wellness program with
city of Louisville, Lincoln Foundation
Engineer
May - July 2010
Net Results Inc. Louisville, KY
Performed Level 1 triage of Alternative Response Technologies for abatement,
containment, and remediation of oil flow due to the BP Deepwater Horizon explosion,
Gulf of Mexico.
Software Security Systems Engineer
Sept. 2008 – Apr.
2010
Ebullient Services Inc. Arlington, TX
Developed front end security gateway for organizational user accounts. Planning, and
designing of security systems using SUN IDM and data base tools.
Teaching Experience
Louisville, KY
Graduate Teaching Assistant
Aug. 2010 TD
Civil and Environmental Engineering Department
 Assisted in grading and teaching Courses
208
 Assisted in developing research proposals for external grants
Courses: CEE 205: Statics (Fall 2010, Spring 2011, Summer 2011)
CEE 370: Engineering Hydraulics (Spring 2012, 2013, 2014)
CEE 422: Steel Design (Fall 2013)
Certifications & Training
LEED Green Associate
31st July 2014 – 30th July 2016
United States Green Building Council
Louisville Ky
Graduate teaching Academy (GTA)
Aug. 2011 – Jan.
2012
 Trained for developing course structures
 Trained for improving interaction with students
 Trained for developing and acquiring latest teaching techniques
Grant Writing Academy (GWA)
Aug. 2013 – Jan.
2014
 Trained for searching, developing, and submission of proposals for extramural
grants
 Trained for developing budget
Department of Environmental Health and Safety
NIH Guidelines program; Biosafety Training (BSL1/BSL2); OSHA Training
Awards
Speed Graduate Scholarship
Fall 2007; Spring
2008
CODRE Scholarship
2012-2013
Martha & Frank Diebold Award
April 2014
Nominated for Community Engagement Award 2014 in student category
Computer Skills
Proficient in MS Office, AutoCAD, STAAD-Pro, HCS, TNM, ANSYS, HEC-RAS,
WMS, HMS, Arc MAP, Solid Works, Data Base tools, Photoshop, Adobe Flash
Posters/Presentations
ullapalli, Venkata D., French, ark N., and Rockaway, Thomas D. “Stream Flow
Augmentation Using Treated Filer Wash Water”, World Environmental & Water
Resources Congress, Palm Springs, California, May 22-26, 2011.
ullapalli, Venkata D. and French, ark N., “Treated Filter Backwash Water as
Source of Streamflow Augmentation” 27th Annual WateReuse Symposium, Ft.
Lauderdale, Florida, September 9-12, 2012.
ullapalli, Venkata D. and French, ark N., “Natural Methods for Treating and
Disposing of Industrial Waste Water for Urban Stream Restoration”, KY/TN Water
Professional Conference, Louisville, KY, July 2013.
ullapalli, Venkata D. “ reen Concepts in Water Treatment”, Uof Sustainability
Scholars Roundtable, University of Louisville, November 20th 2014.
209
ullapalli, Venkata D. and French, ark N., “Solar UV Disinfection of Open
Channel Flowing Water” 14th annual conference National Council for science and the
environment, Washington D.C., January 28-30, 2014.
Memberships
Member of ASCE Louisville student chapter
Student Member KY Science Foundation
24 PDHs by attending professional conferences and meetings
210

Community engagement, environmental education, and public

Transcription

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